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Erik Cambria

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affiliation: Nanyang Technological University, Singapore

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2020 – today

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2025
[j244]
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Zhaoxia Wang, Donghao Huang, Jingfeng Cui, Xinyue Zhang, Seng-Beng Ho, Erik Cambria:
A review of Chinese sentiment analysis: subjects, methods, and trends. Artif. Intell. Rev. 58(3): 75 (2025)
[j243]
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Xianxun Zhu, Zhaozhao Liu, Erik Cambria, Xiaohan Yu, Xuhui Fan, Hui Chen, Rui Wang:
A client-server based recognition system: Non-contact single/multiple emotional and behavioral state assessment methods. Comput. Methods Programs Biomed. 260: 108564 (2025)
[j242]
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Rui Mao, Guanyi Chen, Xiao Li, Mengshi Ge, Erik Cambria:
A Comparative Analysis of Metaphorical Cognition in ChatGPT and Human Minds. Cogn. Comput. 17(1): 35 (2025)
[j241]
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Mengshi Ge, Rui Mao, Erik Cambria:
Discovering the Cognitive Bias of Toxic Language Through Metaphorical Concept Mappings. Cogn. Comput. 17(1): 65 (2025)
[j240]
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Yuansheng Ma, Dong Zhang, Shoushan Li, Erik Cambria, Guodong Zhou:
Ueco: Unified editing chain for efficient appearance transfer with multimodality-guided diffusion. Expert Syst. Appl. 270: 126510 (2025)
[j239]
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Hao Liu, Runguo Wei, Geng Tu, Jiali Lin, Dazhi Jiang, Erik Cambria:
Knowing What and Why: Causal emotion entailment for emotion recognition in conversations. Expert Syst. Appl. 274: 126924 (2025)
[j238]
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Rui Mao, Mengshi Ge, Sooji Han, Wei Li, Kai He, Luyao Zhu, Erik Cambria:
A survey on pragmatic processing techniques. Inf. Fusion 114: 102712 (2025)
[j237]
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  - journals/inffus/OngMSFCSM25
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Keane Ong, Rui Mao, Ranjan Satapathy, Ricardo Shirota Filho, Erik Cambria, Johan Sulaeman, Gianmarco Mengaldo:
Explainable natural language processing for corporate sustainability analysis. Inf. Fusion 115: 102726 (2025)
[j236]
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Kelvin Du, Yazhi Zhao, Rui Mao, Frank Xing, Erik Cambria:
Natural language processing in finance: A survey. Inf. Fusion 115: 102755 (2025)
[j235]
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  - journals/inffus/LinZMHMHPCF25
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Qika Lin, Yifan Zhu, Xin Mei, Ling Huang, Jingying Ma, Kai He, Zhen Peng, Erik Cambria, Mengling Feng:
Has multimodal learning delivered universal intelligence in healthcare? A comprehensive survey. Inf. Fusion 116: 102795 (2025)
[j234]
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  - journals/inffus/ShenCWCZ25
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Tiesunlong Shen, Erik Cambria, Jin Wang, Yi Cai, Xuejie Zhang:
Insight at the right spot: Provide decisive subgraph information to Graph LLM with reinforcement learning. Inf. Fusion 117: 102860 (2025)
[j233]
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  - journals/inffus/HeMLRLFC25
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Kai He, Rui Mao, Qika Lin, Yucheng Ruan, Xiang Lan, Mengling Feng, Erik Cambria:
A survey of large language models for healthcare: from data, technology, and applications to accountability and ethics. Inf. Fusion 118: 102963 (2025)
[j232]
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  - journals/inffus/WangMLCM25
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Tao Wang, Rui Mao, Shuang Liu, Erik Cambria, Dong Ming:
Explainable multi-frequency and multi-region fusion model for affective brain-computer interfaces. Inf. Fusion 118: 102971 (2025)
[j231]
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  - journals/isci/LiangLZHJC25
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Jiazhen Liang, Wai Li, Qingshan Zhong, Jun Huang, Dazhi Jiang, Erik Cambria:
Learning chain for clause awareness: Triplex-contrastive learning for emotion recognition in conversations. Inf. Sci. 705: 121969 (2025)
[j230]
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  - journals/staeors/ChengCLCW25
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Kangda Cheng, Erik Cambria, Jinlong Liu, Yushi Chen, Zhilu Wu:
KE-RSIC: Remote Sensing Image Captioning Based on Knowledge Embedding. IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens. 18: 4286-4304 (2025)
[c222]
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  - conf/coling/ShenWZC25
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Tiesunlong Shen, Jin Wang, Xuejie Zhang, Erik Cambria:
Reasoning with Trees: Faithful Question Answering over Knowledge Graph. COLING 2025: 3138-3157
[i115]
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  - journals/corr/abs-2501-01987
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Mohammad Nadeem, Shahab Saquib Sohail, Erik Cambria, Björn W. Schuller, Amir Hussain:
Gender Bias in Text-to-Video Generation Models: A case study of Sora. CoRR abs/2501.01987 (2025)
[i114]
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  - journals/corr/abs-2501-12433
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Tabinda Aman, Mohammad Nadeem, Shahab Saquib Sohail, Mohammad Anas, Erik Cambria:
Owls are wise and foxes are unfaithful: Uncovering animal stereotypes in vision-language models. CoRR abs/2501.12433 (2025)
[i113]
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  - journals/corr/abs-2501-15720
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Keane Ong, Rui Mao, Frank Xing, Ranjan Satapathy, Johan Sulaeman, Erik Cambria, Gianmarco Mengaldo:
ESGSenticNet: A Neurosymbolic Knowledge Base for Corporate Sustainability Analysis. CoRR abs/2501.15720 (2025)
[i112]
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  - journals/corr/abs-2502-00681
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Qika Lin, Zhen Peng, Kaize Shi, Kai He, Yiming Xu, Erik Cambria, Mengling Feng:
A Survey of Quantized Graph Representation Learning: Connecting Graph Structures with Large Language Models. CoRR abs/2502.00681 (2025)
[i111]
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  - journals/corr/abs-2502-04976
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Han Zhang, Zixiang Meng, Meng Luo, Hong Han, Lizi Liao, Erik Cambria, Hao Fei:
Towards Multimodal Empathetic Response Generation: A Rich Text-Speech-Vision Avatar-based Benchmark. CoRR abs/2502.04976 (2025)
[i110]
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  - journals/corr/abs-2502-15821
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Keane Ong, Rui Mao, Deeksha Varshney, Erik Cambria, Gianmarco Mengaldo:
Towards Robust ESG Analysis Against Greenwashing Risks: Aspect-Action Analysis with Cross-Category Generalization. CoRR abs/2502.15821 (2025)
2024
[j229]
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  - journals/ac/JayaramanATC24
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Ashok Kumar Jayaraman, Gayathri Ananthakrishnan, Tina Esther Trueman, Erik Cambria:
Chapter Four - Text-based personality prediction using XLNet. Adv. Comput. 132: 49-65 (2024)
[j228]
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  - journals/cogcom/DuongRLMMC24
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Cuc Duong, Vethavikashini Chithrra Raghuram, Amos Lee, Rui Mao, Gianmarco Mengaldo, Erik Cambria:
Neurosymbolic AI for Mining Public Opinions about Wildfires. Cogn. Comput. 16(4): 1531-1553 (2024)
[j227]
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  - journals/cogcom/ZhangMC24
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Xulang Zhang, Rui Mao, Erik Cambria:
Granular Syntax Processing with Multi-Task and Curriculum Learning. Cogn. Comput. 16(6): 3020-3034 (2024)
[j226]
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  - journals/cogcom/MaoLLCH24
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Rui Mao, Qian Liu, Xiao Li, Erik Cambria, Amir Hussain:
Guest Editorial: Cognitive Analysis for Humans and AI. Cogn. Comput. 16(6): 3316-3318 (2024)
[j225]
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  - journals/cogcom/ChaturvediPCWD24
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Iti Chaturvedi, Vlad Pandelea, Erik Cambria, Roy E. Welsch, Bithin Datta:
Barrier Function to Skin Elasticity in Talking Head. Cogn. Comput. 16(6): 3405-3416 (2024)
[j224]
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Qian Liu, Sooji Han, Erik Cambria, Yang Li, Kenneth Kwok:
PrimeNet: A Framework for Commonsense Knowledge Representation and Reasoning Based on Conceptual Primitives. Cogn. Comput. 16(6): 3429-3456 (2024)
[j223]
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  - journals/csur/DuXMC24
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Kelvin Du, Frank Xing, Rui Mao, Erik Cambria:
Financial Sentiment Analysis: Techniques and Applications. ACM Comput. Surv. 56(9): 220:1-220:42 (2024)
[j222]
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  - journals/es/ChaturvediSLC24
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Iti Chaturvedi, Ranjan Satapathy, Curtis Lynch, Erik Cambria:
Predicting word vectors for microtext. Expert Syst. J. Knowl. Eng. 41(8) (2024)
[j221]
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  - journals/es/GandhiAASLCPH24
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Ankita Gandhi, Param Ahir, Kinjal Adhvaryu, Pooja Shah, Ritika Lohiya, Erik Cambria, Soujanya Poria, Amir Hussain:
Hate speech detection: A comprehensive review of recent works. Expert Syst. J. Knowl. Eng. 41(8) (2024)
[j220]
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  - journals/es/BounhasECHC24
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Myriam Bounhas, Bilel Elayeb, Amina Chouigui, Amir Hussain, Erik Cambria:
Arabic text classification based on analogical proportions. Expert Syst. J. Knowl. Eng. 41(10) (2024)
[j219]
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  - journals/expert/AnasSSCH24
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Mohammad Anas, Anam Saiyeda, Shahab Saquib Sohail, Erik Cambria, Amir Hussain:
Can Generative AI Models Extract Deeper Sentiments as Compared to Traditional Deep Learning Algorithms? IEEE Intell. Syst. 39(2): 5-10 (2024)
[j218]
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  - journals/expert/KazienkoC24
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Przemyslaw Kazienko, Erik Cambria:
Toward Responsible Recommender Systems. IEEE Intell. Syst. 39(3): 5-12 (2024)
[j217]
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  - journals/expert/TuNXLC24
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Geng Tu, Taiyu Niu, Ruifeng Xu, Bin Liang, Erik Cambria:
AdaCLF: An Adaptive Curriculum Learning Framework for Emotional Support Conversation. IEEE Intell. Syst. 39(4): 5-11 (2024)
[j216]
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  - journals/expert/NadeemJSCH24
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Mohammad Nadeem, Laeeba Javed, Shahab Saquib Sohail, Erik Cambria, Amir Hussain:
Are Foundation Models the Next-Generation Social Media Content Moderators? IEEE Intell. Syst. 39(6): 70-80 (2024)
[j215]
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  - journals/ijon/JiangLTWC24
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Dazhi Jiang, Hao Liu, Geng Tu, Runguo Wei, Erik Cambria:
Self-supervised utterance order prediction for emotion recognition in conversations. Neurocomputing 577: 127370 (2024)
[j214]
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Rui Mao, Kai He, Xulang Zhang, Guanyi Chen, Jinjie Ni, Zonglin Yang, Erik Cambria:
A survey on semantic processing techniques. Inf. Fusion 101: 101988 (2024)
[j213]
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Yu Ma, Rui Mao, Qika Lin, Peng Wu, Erik Cambria:
Quantitative stock portfolio optimization by multi-task learning risk and return. Inf. Fusion 104: 102165 (2024)
[j212]
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  - journals/inffus/FanLMC24
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Chunxiao Fan, Jie Lin, Rui Mao, Erik Cambria:
Fusing pairwise modalities for emotion recognition in conversations. Inf. Fusion 106: 102306 (2024)
[j211]
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  - journals/inffus/LiuLDMC24
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Mengyue Liu, Jun Liu, Yixiang Dong, Rui Mao, Erik Cambria:
Interest-driven community detection on attributed heterogeneous information networks. Inf. Fusion 111: 102525 (2024)
[j210]
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  - journals/kbs/VarshneyEC24
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Deeksha Varshney, Asif Ekbal, Erik Cambria:
Emotion-and-knowledge grounded response generation in an open-domain dialogue setting. Knowl. Based Syst. 284: 111173 (2024)
[j209]
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Xiaoshi Zhong, Chenyu Jin, Mengyu An, Erik Cambria:
XTime: A general rule-based method for time expression recognition and normalization. Knowl. Based Syst. 297: 111921 (2024)
[j208]
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Weilun Yu, Chengming Li, Xiping Hu, Wenhua Zhu, Erik Cambria, Dazhi Jiang:
Dialogue emotion model based on local-global context encoder and commonsense knowledge fusion attention. Int. J. Mach. Learn. Cybern. 15(7): 2811-2825 (2024)
[j207]
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Phuong Le-Hong, Erik Cambria:
Integrating graph embedding and neural models for improving transition-based dependency parsing. Neural Comput. Appl. 36(6): 2999-3016 (2024)
[j206]
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  - journals/taffco/DiwaliSDGCH24
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Arwa Diwali, Kawther Saeedi, Kia Dashtipour, Mandar Gogate, Erik Cambria, Amir Hussain:
Sentiment Analysis Meets Explainable Artificial Intelligence: A Survey on Explainable Sentiment Analysis. IEEE Trans. Affect. Comput. 15(3): 837-846 (2024)
[j205]
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Bin Liang, Lin Gui, Yulan He, Erik Cambria, Ruifeng Xu:
Fusion and Discrimination: A Multimodal Graph Contrastive Learning Framework for Multimodal Sarcasm Detection. IEEE Trans. Affect. Comput. 15(4): 1874-1888 (2024)
[j204]
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  - journals/taffco/AminMCS24
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Mostafa M. Amin, Rui Mao, Erik Cambria, Björn W. Schuller:
A Wide Evaluation of ChatGPT on Affective Computing Tasks. IEEE Trans. Affect. Comput. 15(4): 2204-2212 (2024)
[j203]
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Qian Liu, Xiubo Geng, Yu Wang, Erik Cambria, Daxin Jiang:
Disentangled Retrieval and Reasoning for Implicit Question Answering. IEEE Trans. Neural Networks Learn. Syst. 35(6): 7804-7815 (2024)
[j202]
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Kai He, Rui Mao, Yucheng Huang, Tieliang Gong, Chen Li, Erik Cambria:
Template-Free Prompting for Few-Shot Named Entity Recognition via Semantic-Enhanced Contrastive Learning. IEEE Trans. Neural Networks Learn. Syst. 35(12): 18357-18369 (2024)
[c221]
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  - conf/acl/WeiXYLC24
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Xiao Wei, Qi Xu, Hang Yu, Qian Liu, Erik Cambria:
Through the MUD: A Multi-Defendant Charge Prediction Benchmark with Linked Crime Elements. ACL (1) 2024: 2864-2878
[c220]
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Xulang Zhang, Rui Mao, Erik Cambria:
SenticVec: Toward Robust and Human-Centric Neurosymbolic Sentiment Analysis. ACL (Findings) 2024: 4851-4863
[c219]
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Wei Jie Yeo, Ranjan Satapathy, Erik Cambria:
Plausible Extractive Rationalization through Semi-Supervised Entailment Signal. ACL (Findings) 2024: 5182-5192
[c218]
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Rui Mao, Kai He, Claudia Ong, Qian Liu, Erik Cambria:
MetaPro 2.0: Computational Metaphor Processing on the Effectiveness of Anomalous Language Modeling. ACL (Findings) 2024: 9891-9908
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An Quang Tang, Xiuzhen Zhang, Minh Ngoc Dinh, Erik Cambria:
Prompted Aspect Key Point Analysis for Quantitative Review Summarization. ACL (1) 2024: 10691-10708
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Zonglin Yang, Xinya Du, Junxian Li, Jie Zheng, Soujanya Poria, Erik Cambria:
Large Language Models for Automated Open-domain Scientific Hypotheses Discovery. ACL (Findings) 2024: 13545-13565
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Kelvin Du, Rui Mao, Frank Xing, Erik Cambria:
Explainable Stock Price Movement Prediction using Contrastive Learning. CIKM 2024: 529-537
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Liang Liu, Dong Zhang, Shoushan Li, Guodong Zhou, Erik Cambria:
Two Heads are Better than One: Zero-shot Cognitive Reasoning via Multi-LLM Knowledge Fusion. CIKM 2024: 1462-1472
[c213]
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Rui Mao, Guanyi Chen, Xulang Zhang, Frank Guerin, Erik Cambria:
GPTEval: A Survey on Assessments of ChatGPT and GPT-4. LREC/COLING 2024: 7844-7866
[c212]
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Tan Yue, Xuzhao Shi, Rui Mao, Zonghai Hu, Erik Cambria:
SarcNet: A Multilingual Multimodal Sarcasm Detection Dataset. LREC/COLING 2024: 14325-14335
[c211]
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Zonglin Yang, Li Dong, Xinya Du, Hao Cheng, Erik Cambria, Xiaodong Liu, Jianfeng Gao, Furu Wei:
Language Models as Inductive Reasoners. EACL (1) 2024: 209-225
[c210]
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Zhihao Zhang, Sophia Yat Mei Lee, Junshuang Wu, Dong Zhang, Shoushan Li, Erik Cambria, Guodong Zhou:
Cross-domain NER with Generated Task-Oriented Knowledge: An Empirical Study from Information Density Perspective. EMNLP 2024: 1595-1609
[c209]
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Luwei Xiao, Rui Mao, Xulang Zhang, Liang He, Erik Cambria:
Vanessa: Visual Connotation and Aesthetic Attributes Understanding Network for Multimodal Aspect-based Sentiment Analysis. EMNLP (Findings) 2024: 11486-11500
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Wei Jie Yeo, Teddy Ferdinan, Przemyslaw Kazienko, Ranjan Satapathy, Erik Cambria:
Self-training Large Language Models through Knowledge Detection. EMNLP (Findings) 2024: 15033-15045
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Amirhossein Aminimehr, Pouya Khani, Amirali Molaei, Amirmohammad Kazemeini, Erik Cambria:
TbExplain: A Text-Based Explanation Method for Scene Classification Models With the Statistical Prediction Correction. GUIDE-AI@SIGMOD 2024: 54-60
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Erik Cambria, Xulang Zhang, Rui Mao, Melvin Chen, Kenneth Kwok:
SenticNet 8: Fusing Emotion AI and Commonsense AI for Interpretable, Trustworthy, and Explainable Affective Computing. HCI (71) 2024: 197-216
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Luyao Zhu, Rui Mao, Erik Cambria, Bernard J. Jansen:
Neurosymbolic AI for Personalized Sentiment Analysis. HCI (71) 2024: 269-290
[c204]
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Rui Mao, Qika Lin, Qiawen Liu, Gianmarco Mengaldo, Erik Cambria:
Understanding Public Perception Towards Weather Disasters Through the Lens of Metaphor. IJCAI 2024: 7394-7402
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Kelvin Du, Rui Mao, Frank Xing, Erik Cambria:
A Dynamic Dual-Graph Neural Network for Stock Price Movement Prediction. IJCNN 2024: 1-8
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Xulang Zhang, Rui Mao, Erik Cambria:
Multilingual Emotion Recognition: Discovering the Variations of Lexical Semantics between Languages. IJCNN 2024: 1-9
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Erik Cambria:
7 Pillars for the Future of AI (abstract). LaCATODA@PRICAI 2024: 93
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Xin Mei, Rui Mao, Xiaoyan Cai, Libin Yang, Erik Cambria:
Medical Report Generation via Multimodal Spatio-Temporal Fusion. ACM Multimedia 2024: 4699-4708
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Meng Luo, Hao Fei, Bobo Li, Shengqiong Wu, Qian Liu, Soujanya Poria, Erik Cambria, Mong-Li Lee, Wynne Hsu:
PanoSent: A Panoptic Sextuple Extraction Benchmark for Multimodal Conversational Aspect-based Sentiment Analysis. ACM Multimedia 2024: 7667-7676
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Zheng Lian, Bin Liu, Rui Liu, Kele Xu, Erik Cambria, Guoying Zhao, Björn W. Schuller, Jianhua Tao:
MRAC'24 Track 2: 2nd International Workshop on Multimodal and Responsible Affective Computing. MRAC@MM 2024: 39-40
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Zheng Lian, Haiyang Sun, Licai Sun, Zhuofan Wen, Siyuan Zhang, Shun Chen, Hao Gu, Jinming Zhao, Ziyang Ma, Xie Chen, Jiangyan Yi, Rui Liu, Kele Xu, Bin Liu, Erik Cambria, Guoying Zhao, Björn W. Schuller, Jianhua Tao:
MER 2024: Semi-Supervised Learning, Noise Robustness, and Open-Vocabulary Multimodal Emotion Recognition. MRAC@MM 2024: 41-48
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Shahin Amiriparian, Lukas Christ, Alexander Kathan, Maurice Gerczuk, Niklas Müller, Steffen Klug, Lukas Stappen, Andreas König, Erik Cambria, Björn W. Schuller, Simone Eulitz:
The MuSe 2024 Multimodal Sentiment Analysis Challenge: Social Perception and Humor Recognition. MuSe@ACM Multimedia 2024: 1-9
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Lukas Christ, Shahin Amiriparian, Andreas König, Simone Eulitz, Erik Cambria, Björn W. Schuller:
MuSe '24: The 5th Multimodal Sentiment Analysis Challenge and Workshop: Social Perception & Humor. MuSe@ACM Multimedia 2024: 10-11
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Wei Jie Yeo, Ranjan Satapathy, Rich Siow Mong Goh, Erik Cambria:
How Interpretable are Reasoning Explanations from Prompting Large Language Models? NAACL-HLT (Findings) 2024: 2148-2164
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Erik Cambria, Balázs Gulyás, Joyce S. Pang, Nigel V. Marsh, Mythily Subramaniam:
Explainable AI for Stress and Depression Detection in the Cyberspace and Beyond. PAKDD (Workshops) 2024: 108-120
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Shivani Kumar, Md. Shad Akhtar, Erik Cambria, Tanmoy Chakraborty:
SemEval 2024 - Task 10: Emotion Discovery and Reasoning its Flip in Conversation (EDiReF). SemEval@NAACL 2024: 1933-1946
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Fanfan Wang, Heqing Ma, Rui Xia, Jianfei Yu, Erik Cambria:
SemEval-2024 Task 3: Multimodal Emotion Cause Analysis in Conversations. SemEval@NAACL 2024: 2039-2050
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Jianhua Tao, Shreya Ghosh, Zheng Lian, Zhixi Cai, Björn W. Schuller, Abhinav Dhall, Guoying Zhao, Dimitrios Kollias, Erik Cambria, Roland Goecke, Tom Gedeon:
Proceedings of the 2nd International Workshop on Multimodal and Responsible Affective Computing, MRAC 2024, Melbourne VIC, Australia, 28 October 2024- 1 November 2024. ACM 2024, ISBN 979-8-4007-1203-6 [contents]
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Shahin Amiriparian, Lukas Christ, Simone Eulitz, Andreas König, Erik Cambria, Björn W. Schuller:
Proceedings of the 5th on Multimodal Sentiment Analysis Challenge and Workshop: Social Perception and Humor, MuSe2024, Melbourne, VIC, Australia, 28 October 2024- 1 November 2024. ACM 2024, ISBN 979-8-4007-1199-2 [contents]
[i109]
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Wei Jie Yeo, Ranjan Satapathy, Erik Cambria:
Plausible Extractive Rationalization through Semi-Supervised Entailment Signal. CoRR abs/2402.08479 (2024)
[i108]
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Wei Jie Yeo, Ranjan Satapathy, Rick Siow Mong Goh, Erik Cambria:
How Interpretable are Reasoning Explanations from Prompting Large Language Models? CoRR abs/2402.11863 (2024)
[i107]
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Shivani Kumar, Md. Shad Akhtar, Erik Cambria, Tanmoy Chakraborty:
SemEval 2024 - Task 10: Emotion Discovery and Reasoning its Flip in Conversation (EDiReF). CoRR abs/2402.18944 (2024)
[i106]
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  - journals/corr/abs-2404-17113
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Zheng Lian, Haiyang Sun, Licai Sun, Zhuofan Wen, Siyuan Zhang, Shun Chen, Hao Gu, Jinming Zhao, Ziyang Ma, Xie Chen, Jiangyan Yi, Rui Liu, Kele Xu, Bin Liu, Erik Cambria, Guoying Zhao, Björn W. Schuller, Jianhua Tao:
MER 2024: Semi-Supervised Learning, Noise Robustness, and Open-Vocabulary Multimodal Emotion Recognition. CoRR abs/2404.17113 (2024)
[i105]
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  - journals/corr/abs-2405-13049
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Fanfan Wang, Heqing Ma, Jianfei Yu, Rui Xia, Erik Cambria:
SemEval-2024 Task 3: Multimodal Emotion Cause Analysis in Conversations. CoRR abs/2405.13049 (2024)
[i104]
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  - journals/corr/abs-2406-07753
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Shahin Amiriparian, Lukas Christ, Alexander Kathan, Maurice Gerczuk, Niklas Müller, Steffen Klug, Lukas Stappen, Andreas König, Erik Cambria, Björn W. Schuller, Simone Eulitz:
The MuSe 2024 Multimodal Sentiment Analysis Challenge: Social Perception and Humor Recognition. CoRR abs/2406.07753 (2024)
[i103]
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  - journals/corr/abs-2406-11275
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Wei Jie Yeo, Teddy Ferdinan, Przemyslaw Kazienko, Ranjan Satapathy, Erik Cambria:
Self-training Large Language Models through Knowledge Detection. CoRR abs/2406.11275 (2024)
[i102]
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  - journals/corr/abs-2406-15177
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Hao Fei, Han Zhang, Bin Wang, Lizi Liao, Qian Liu, Erik Cambria:
EmpathyEar: An Open-source Avatar Multimodal Empathetic Chatbot. CoRR abs/2406.15177 (2024)
[i101]
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An Quang Tang, Xiuzhen Zhang, Minh Ngoc Dinh, Erik Cambria:
Prompted Aspect Key Point Analysis for Quantitative Review Summarization. CoRR abs/2407.14049 (2024)
[i100]
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  - journals/corr/abs-2407-15248
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Erik Cambria, Lorenzo Malandri, Fabio Mercorio, Navid Nobani, Andrea Seveso:
XAI meets LLMs: A Survey of the Relation between Explainable AI and Large Language Models. CoRR abs/2407.15248 (2024)
[i99]
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Keane Ong, Rui Mao, Ranjan Satapathy, Ricardo Shirota Filho, Erik Cambria, Johan Sulaeman, Gianmarco Mengaldo:
Explainable Natural Language Processing for Corporate Sustainability Analysis. CoRR abs/2407.17487 (2024)
[i98]
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  - journals/corr/abs-2408-09481
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Meng Luo, Hao Fei, Bobo Li, Shengqiong Wu, Qian Liu, Soujanya Poria, Erik Cambria, Mong-Li Lee, Wynne Hsu:
PanoSent: A Panoptic Sextuple Extraction Benchmark for Multimodal Conversational Aspect-based Sentiment Analysis. CoRR abs/2408.09481 (2024)
[i97]
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  - journals/corr/abs-2408-12880
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Qika Lin, Yifan Zhu, Xin Mei, Ling Huang, Jingying Ma, Kai He, Zhen Peng, Erik Cambria, Mengling Feng:
Has Multimodal Learning Delivered Universal Intelligence in Healthcare? A Comprehensive Survey. CoRR abs/2408.12880 (2024)
[i96]
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  - journals/corr/abs-2409-00105
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Mohammad Nadeem, Shahab Saquib Sohail, Erik Cambria, Björn W. Schuller, Amir Hussain:
Negation Blindness in Large Language Models: Unveiling the NO Syndrome in Image Generation. CoRR abs/2409.00105 (2024)
[i95]
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  - journals/corr/abs-2410-07076
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Zonglin Yang, Wanhao Liu, Ben Gao, Tong Xie, Yuqiang Li, Wanli Ouyang, Soujanya Poria, Erik Cambria, Dongzhan Zhou:
MOOSE-Chem: Large Language Models for Rediscovering Unseen Chemistry Scientific Hypotheses. CoRR abs/2410.07076 (2024)
[i94]
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  - journals/corr/abs-2410-14155
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Wei Jie Yeo, Ranjan Satapathy, Erik Cambria:
Towards Faithful Natural Language Explanations: A Study Using Activation Patching in Large Language Models. CoRR abs/2410.14155 (2024)
[i93]
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  - journals/corr/abs-2412-02508
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Haidong Xu, Meishan Zhang, Hao Ju, Zhedong Zheng, Hongyuan Zhu, Erik Cambria, Min Zhang, Hao Fei:
Towards Rich Emotions in 3D Avatars: A Text-to-3D Avatar Generation Benchmark. CoRR abs/2412.02508 (2024)
2023
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  - journals/air/LatifCPSAC23
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Siddique Latif, Heriberto Cuayáhuitl, Farrukh Pervez, Fahad Shamshad, Hafiz Shehbaz Ali, Erik Cambria:
A survey on deep reinforcement learning for audio-based applications. Artif. Intell. Rev. 56(3): 2193-2240 (2023)
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Jinjie Ni, Tom Young, Vlad Pandelea, Fuzhao Xue, Erik Cambria:
Recent advances in deep learning based dialogue systems: a systematic survey. Artif. Intell. Rev. 56(4): 3055-3155 (2023)
[j199]
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Xulang Zhang, Rui Mao, Erik Cambria:
A survey on syntactic processing techniques. Artif. Intell. Rev. 56(6): 5645-5728 (2023)
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Jingfeng Cui, Zhaoxia Wang, Seng-Beng Ho, Erik Cambria:
Survey on sentiment analysis: evolution of research methods and topics. Artif. Intell. Rev. 56(8): 8469-8510 (2023)
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Xiaoshi Zhong, Erik Cambria:
Time expression recognition and normalization: a survey. Artif. Intell. Rev. 56(9): 9115-9140 (2023)
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Ruicheng Liu, Rui Mao, Anh Tuan Luu, Erik Cambria:
A brief survey on recent advances in coreference resolution. Artif. Intell. Rev. 56(12): 14439-14481 (2023)
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Mengshi Ge, Rui Mao, Erik Cambria:
A survey on computational metaphor processing techniques: from identification, interpretation, generation to application. Artif. Intell. Rev. 56(S2): 1829-1895 (2023)
[j194]
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Javier Torregrosa, Sergio D'Antonio-Maceiras, Guillermo Villar-Rodríguez, Amir Hussain, Erik Cambria, David Camacho:
A Mixed Approach for Aggressive Political Discourse Analysis on Twitter. Cogn. Comput. 15(2): 440-465 (2023)
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Zhaoxia Wang, Zhenda Hu, Fang Li, Seng-Beng Ho, Erik Cambria:
Learning-Based Stock Trending Prediction by Incorporating Technical Indicators and Social Media Sentiment. Cogn. Comput. 15(3): 1092-1102 (2023)
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Seham Basabain, Erik Cambria, Khalid Alomar, Amir Hussain:
Enhancing Arabic-text feature extraction utilizing label-semantic augmentation in few/zero-shot learning. Expert Syst. J. Knowl. Eng. 40(8) (2023)
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Kai He, Yucheng Huang, Rui Mao, Tieliang Gong, Chen Li, Erik Cambria:
Virtual prompt pre-training for prototype-based few-shot relation extraction. Expert Syst. Appl. 213(Part): 118927 (2023)
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Mostafa M. Amin, Erik Cambria, Björn W. Schuller:
Will Affective Computing Emerge From Foundation Models and General Artificial Intelligence? A First Evaluation of ChatGPT. IEEE Intell. Syst. 38(2): 15-23 (2023)
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Mostafa M. Amin, Erik Cambria, Björn W. Schuller:
Can ChatGPT's Responses Boost Traditional Natural Language Processing? IEEE Intell. Syst. 38(5): 5-11 (2023)
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Erik Cambria, Rui Mao, Melvin Chen, Zhaoxia Wang, Seng-Beng Ho:
Seven Pillars for the Future of Artificial Intelligence. IEEE Intell. Syst. 38(6): 62-69 (2023)
[j187]
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Tian-Hui You, Ling Ling Tao, Erik Cambria:
A Hotel Ranking Model Through Online Reviews With Aspect-Based Sentiment Analysis. Int. J. Inf. Technol. Decis. Mak. 22(1): 89-113 (2023)
[j186]
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Qika Lin, Rui Mao, Jun Liu, Fangzhi Xu, Erik Cambria:
Fusing topology contexts and logical rules in language models for knowledge graph completion. Inf. Fusion 90: 253-264 (2023)
[j185]
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Jintao Wen, Dazhi Jiang, Geng Tu, Cheng Liu, Erik Cambria:
Dynamic interactive multiview memory network for emotion recognition in conversation. Inf. Fusion 91: 123-133 (2023)
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Mauajama Firdaus, Asif Ekbal, Erik Cambria:
Multitask learning for multilingual intent detection and slot filling in dialogue systems. Inf. Fusion 91: 299-315 (2023)
[j183]
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Ankita Gandhi, Kinjal Adhvaryu, Soujanya Poria, Erik Cambria, Amir Hussain:
Multimodal sentiment analysis: A systematic review of history, datasets, multimodal fusion methods, applications, challenges and future directions. Inf. Fusion 91: 424-444 (2023)
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Yu Ma, Rui Mao, Qika Lin, Peng Wu, Erik Cambria:
Multi-source aggregated classification for stock price movement prediction. Inf. Fusion 91: 515-528 (2023)
[j181]
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Tan Yue, Rui Mao, Heng Wang, Zonghai Hu, Erik Cambria:
KnowleNet: Knowledge fusion network for multimodal sarcasm detection. Inf. Fusion 100: 101921 (2023)
[j180]
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Jialun Wu, Kai He, Rui Mao, Chen Li, Erik Cambria:
MEGACare: Knowledge-guided multi-view hypergraph predictive framework for healthcare. Inf. Fusion 100: 101939 (2023)
[j179]
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Erik Cambria, Lorenzo Malandri, Fabio Mercorio, Mario Mezzanzanica, Navid Nobani:
A survey on XAI and natural language explanations. Inf. Process. Manag. 60(1): 103111 (2023)
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Qian Liu, Rui Mao, Xiubo Geng, Erik Cambria:
Semantic matching in machine reading comprehension: An empirical study. Inf. Process. Manag. 60(2): 103145 (2023)
[j177]
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Mohammad Al-Smadi, Mahmoud M. Hammad, Sa'ad A. Al-Zboon, Saja AL-Tawalbeh, Erik Cambria:
Gated recurrent unit with multilingual universal sentence encoder for Arabic aspect-based sentiment analysis. Knowl. Based Syst. 261: 107540 (2023)
[j176]
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Xiaoshi Zhong, Xiang Yu, Erik Cambria, Jagath C. Rajapakse:
Marshall-Olkin power-law distributions in length-frequency of entities. Knowl. Based Syst. 279: 110942 (2023)
[j175]
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Phuong Le-Hong, Erik Cambria:
A semantics-aware approach for multilingual natural language inference. Lang. Resour. Evaluation 57(2): 611-639 (2023)
[j174]
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Zhaoxia Wang, Zhenda Hu, Seng-Beng Ho, Erik Cambria, Ah-Hwee Tan:
MiMuSA - mimicking human language understanding for fine-grained multi-class sentiment analysis. Neural Comput. Appl. 35(21): 15907-15921 (2023)
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Yang Li, Quan Pan, Zhaowen Feng, Erik Cambria:
Few pixels attacks with generative model. Pattern Recognit. 144: 109849 (2023)
[j172]
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Frank Xing, Björn W. Schuller, Iti Chaturvedi, Erik Cambria, Amir Hussain:
Guest Editorial Neurosymbolic AI for Sentiment Analysis. IEEE Trans. Affect. Comput. 14(3): 1711-1715 (2023)
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Kai He, Rui Mao, Tieliang Gong, Chen Li, Erik Cambria:
Meta-Based Self-Training and Re-Weighting for Aspect-Based Sentiment Analysis. IEEE Trans. Affect. Comput. 14(3): 1731-1742 (2023)
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Rui Mao, Qian Liu, Kai He, Wei Li, Erik Cambria:
The Biases of Pre-Trained Language Models: An Empirical Study on Prompt-Based Sentiment Analysis and Emotion Detection. IEEE Trans. Affect. Comput. 14(3): 1743-1753 (2023)
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Wei Li, Yang Li, Vlad Pandelea, Mengshi Ge, Luyao Zhu, Erik Cambria:
ECPEC: Emotion-Cause Pair Extraction in Conversations. IEEE Trans. Affect. Comput. 14(3): 1754-1765 (2023)
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Dazhi Jiang, Runguo Wei, Jintao Wen, Geng Tu, Erik Cambria:
AutoML-Emo: Automatic Knowledge Selection Using Congruent Effect for Emotion Identification in Conversations. IEEE Trans. Affect. Comput. 14(3): 1845-1856 (2023)
[j167]
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Luna Ansari, Shaoxiong Ji, Qian Chen, Erik Cambria:
Ensemble Hybrid Learning Methods for Automated Depression Detection. IEEE Trans. Comput. Soc. Syst. 10(1): 211-219 (2023)
[j166]
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Wei Sun, Shaoxiong Ji, Erik Cambria, Pekka Marttinen:
Multitask Balanced and Recalibrated Network for Medical Code Prediction. ACM Trans. Intell. Syst. Technol. 14(1): 17:1-17:20 (2023)
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Kelvin Du, Frank Xing, Erik Cambria:
Incorporating Multiple Knowledge Sources for Targeted Aspect-based Financial Sentiment Analysis. ACM Trans. Manag. Inf. Syst. 14(3): 23:1-23:24 (2023)
[c190]
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Wei Li, Luyao Zhu, Rui Mao, Erik Cambria:
SKIER: A Symbolic Knowledge Integrated Model for Conversational Emotion Recognition. AAAI 2023: 13121-13129
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Rui Mao, Xiao Li, Kai He, Mengshi Ge, Erik Cambria:
MetaPro Online: A Computational Metaphor Processing Online System. ACL (demo) 2023: 127-135
[c188]
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Qika Lin, Jun Liu, Rui Mao, Fangzhi Xu, Erik Cambria:
TECHS: Temporal Logical Graph Networks for Explainable Extrapolation Reasoning. ACL (1) 2023: 1281-1293
[c187]
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Ran Zhou, Xin Li, Lidong Bing, Erik Cambria, Chunyan Miao:
Improving Self-training for Cross-lingual Named Entity Recognition with Contrastive and Prototype Learning. ACL (1) 2023: 4018-4031
[c186]
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Luyao Zhu, Wei Li, Rui Mao, Vlad Pandelea, Erik Cambria:
PAED: Zero-Shot Persona Attribute Extraction in Dialogues. ACL (1) 2023: 9771-9787
[c185]
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Jinjie Ni, Rui Mao, Zonglin Yang, Han Lei, Erik Cambria:
Finding the Pillars of Strength for Multi-Head Attention. ACL (1) 2023: 14526-14540
[c184]
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  - conf/bics/HoWQC23
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Seng-Beng Ho, Zhaoxia Wang, Boon-Kiat Quek, Erik Cambria:
Knowledge Representation for Conceptual, Motivational, and Affective Processes in Natural Language Communication. BICS 2023: 14-30
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Zonglin Yang, Xinya Du, Erik Cambria, Claire Cardie:
End-to-end Case-Based Reasoning for Commonsense Knowledge Base Completion. EACL 2023: 3491-3504
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Xulang Zhang, Rui Mao, Kai He, Erik Cambria:
Neuro-Symbolic Sentiment Analysis with Dynamic Word Sense Disambiguation. EMNLP (Findings) 2023: 8772-8783
[c181]
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Wei Li, Luyao Zhu, Wei Shao, Zonglin Yang, Erik Cambria:
Task-Aware Self-Supervised Framework for Dialogue Discourse Parsing. EMNLP (Findings) 2023: 14162-14173
[c180]
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  - conf/hci/SalminenJACJ23
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Joni Salminen, Soon-Gyo Jung, Hind A. Al-Merekhi, Erik Cambria, Bernard J. Jansen:
How Can Natural Language Processing and Generative AI Address Grand Challenges of Quantitative User Personas? HCI (53) 2023: 211-231
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Jinjie Ni, Yukun Ma, Wen Wang, Qian Chen, Dianwen Ng, Han Lei, Trung Hieu Nguyen, Chong Zhang, Bin Ma, Erik Cambria:
Adaptive Knowledge Distillation Between Text and Speech Pre-Trained Models. ICASSP 2023: 1-5
[c178]
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Vlad Pandelea, Edoardo Ragusa, Paolo Gastaldo, Erik Cambria:
Selecting Language Models Features VIA Software-Hardware Co-Design. ICASSP 2023: 1-5
[c177]
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  - conf/icdm/KemikOALC23
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Hasan Kemik, Nusret Özates, Meysam Asgari-Chenaghlu, Yang Li, Erik Cambria:
BLM-17m: A Large-Scale Dataset for Black Lives Matter Topic Detection on Twitter. ICDM (Workshops) 2023: 736-743
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  - conf/icdm/LeitterC23
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Zheng Leitter, Erik Cambria:
Non-Fungible Tokens: What Makes Them Valuable? ICDM (Workshops) 2023: 750-756
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  - conf/icdm/NanettiPC23
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Andrea Nanetti, John Pavlopoulos, Erik Cambria:
Sentiment Analysis of Primary Historical Sources. ICDM (Workshops) 2023: 767-772
[c174]
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  - conf/icdm/OngHSCM23
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Keane Ong, Wihan van der Heever, Ranjan Satapathy, Erik Cambria, Gianmarco Mengaldo:
FinXABSA: Explainable Finance through Aspect-Based Sentiment Analysis. ICDM (Workshops) 2023: 773-782
[c173]
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Rui Mao, Kelvin Du, Yu Ma, Luyao Zhu, Erik Cambria:
Discovering the Cognition behind Language: Financial Metaphor Analysis with MetaPro. ICDM 2023: 1211-1216
[c172]
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Ruicheng Liu, Guanyi Chen, Rui Mao, Erik Cambria:
A Multi-task Learning Model for Gold-two-mention Co-reference Resolution. IJCNN 2023: 1-8
[c171]
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  - conf/intenv/Cambria23
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Erik Cambria:
ALLEGET Keynote Remarks: Emerging Topics in Sentiment Analysis. Intelligent Environments (Workshops) 2023: 51-52
[c170]
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Zheng Lian, Haiyang Sun, Licai Sun, Kang Chen, Mingyu Xu, Kexin Wang, Ke Xu, Yu He, Ying Li, Jinming Zhao, Ye Liu, Bin Liu, Jiangyan Yi, Meng Wang, Erik Cambria, Guoying Zhao, Björn W. Schuller, Jianhua Tao:
MER 2023: Multi-label Learning, Modality Robustness, and Semi-Supervised Learning. ACM Multimedia 2023: 9610-9614
[c169]
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Zheng Lian, Erik Cambria, Guoying Zhao, Björn W. Schuller, Jianhua Tao:
MRAC'23: 1st International Workshop on Multimodal and Responsible Affective Computing. ACM Multimedia 2023: 9713-9714
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Shahin Amiriparian, Lukas Christ, Andreas König, Alan Cowen, Eva-Maria Meßner, Erik Cambria, Björn W. Schuller:
MuSe 2023 Challenge: Multimodal Prediction of Mimicked Emotions, Cross-Cultural Humour, and Personalised Recognition of Affects. ACM Multimedia 2023: 9723-9725
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Lukas Christ, Shahin Amiriparian, Alice Baird, Alexander Kathan, Niklas Müller, Steffen Klug, Chris Gagne, Panagiotis Tzirakis, Lukas Stappen, Eva-Maria Meßner, Andreas König, Alan Cowen, Erik Cambria, Björn W. Schuller:
The MuSe 2023 Multimodal Sentiment Analysis Challenge: Mimicked Emotions, Cross-Cultural Humour, and Personalisation. MuSe@ACM Multimedia 2023: 1-10
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Kelvin Du, Frank Xing, Rui Mao, Erik Cambria:
FinSenticNet: A Concept-Level Lexicon for Financial Sentiment Analysis. SSCI 2023: 109-114
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Shahin Amiriparian, Lukas Christ, Andreas König, Alan Cowen, Eva-Maria Meßner, Erik Cambria, Björn W. Schuller:
Proceedings of the 4th on Multimodal Sentiment Analysis Challenge and Workshop: Mimicked Emotions, Humour and Personalisation, MuSe 2023, Ottawa, ON, Canada, 2 November 2023. ACM 2023 [contents]
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Keane Ong, Wihan van der Heever, Ranjan Satapathy, Gianmarco Mengaldo, Erik Cambria:
FinXABSA: Explainable Finance through Aspect-Based Sentiment Analysis. CoRR abs/2303.02563 (2023)
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Mostafa M. Amin, Erik Cambria, Björn W. Schuller:
Will Affective Computing Emerge from Foundation Models and General AI? A First Evaluation on ChatGPT. CoRR abs/2303.03186 (2023)
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Jinjie Ni, Yukun Ma, Wen Wang, Qian Chen, Dianwen Ng, Han Lei, Trung Hieu Nguyen, Chong Zhang, Bin Ma, Erik Cambria:
Adaptive Knowledge Distillation between Text and Speech Pre-trained Models. CoRR abs/2303.03600 (2023)
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  - journals/corr/abs-2303-12023
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Zonglin Yang, Xinya Du, Rui Mao, Jinjie Ni, Erik Cambria:
Logical Reasoning over Natural Language as Knowledge Representation: A Survey. CoRR abs/2303.12023 (2023)
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  - journals/corr/abs-2304-08981
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Zheng Lian, Haiyang Sun, Licai Sun, Jinming Zhao, Ye Liu, Bin Liu, Jiangyan Yi, Meng Wang, Erik Cambria, Guoying Zhao, Björn W. Schuller, Jianhua Tao:
MER 2023: Multi-label Learning, Modality Robustness, and Semi-Supervised Learning. CoRR abs/2304.08981 (2023)
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Shaoxiong Ji, Tianlin Zhang, Kailai Yang, Sophia Ananiadou, Erik Cambria, Jörg Tiedemann:
Domain-specific Continued Pretraining of Language Models for Capturing Long Context in Mental Health. CoRR abs/2304.10447 (2023)
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  - journals/corr/abs-2304-11431
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Moloud Abdar, Meenakshi Kollati, Swaraja Kuraparthi, Farhad Pourpanah, Daniel McDuff, Mohammad Ghavamzadeh, Shuicheng Yan, Abduallah Mohamed, Abbas Khosravi, Erik Cambria, Fatih Porikli:
A Review of Deep Learning for Video Captioning. CoRR abs/2304.11431 (2023)
[i85]
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  - journals/corr/abs-2305-03369
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Lukas Christ, Shahin Amiriparian, Alice Baird, Alexander Kathan, Niklas Müller, Steffen Klug, Chris Gagne, Panagiotis Tzirakis, Eva-Maria Meßner, Andreas König, Alan Cowen, Erik Cambria, Björn W. Schuller:
The MuSe 2023 Multimodal Sentiment Analysis Challenge: Mimicked Emotions, Cross-Cultural Humour, and Personalisation. CoRR abs/2305.03369 (2023)
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  - journals/corr/abs-2305-13628
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Ran Zhou, Xin Li, Lidong Bing, Erik Cambria, Chunyan Miao:
Improving Self-training for Cross-lingual Named Entity Recognition with Contrastive and Prototype Learning. CoRR abs/2305.13628 (2023)
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Jinjie Ni, Rui Mao, Zonglin Yang, Han Lei, Erik Cambria:
Finding the Pillars of Strength for Multi-Head Attention. CoRR abs/2305.14380 (2023)
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Fangzhi Xu, Qika Lin, Jiawei Han, Tianzhe Zhao, Jun Liu, Erik Cambria:
Are Large Language Models Really Good Logical Reasoners? A Comprehensive Evaluation From Deductive, Inductive and Abductive Views. CoRR abs/2306.09841 (2023)
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Yang Li, Kangbo Liu, Ranjan Satapathy, Suhang Wang, Erik Cambria:
Recent Developments in Recommender Systems: A Survey. CoRR abs/2306.12680 (2023)
[i80]
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Mostafa M. Amin, Erik Cambria, Björn W. Schuller:
Can ChatGPT's Responses Boost Traditional Natural Language Processing? CoRR abs/2307.04648 (2023)
[i79]
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Amirhossein Aminimehr, Pouya Khani, Amirali Molaei, Amirmohammad Kazemeini, Erik Cambria:
TbExplain: A Text-based Explanation Method for Scene Classification Models with the Statistical Prediction Correction. CoRR abs/2307.10003 (2023)
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Amirhossein Aminimehr, Amirali Molaei, Erik Cambria:
EnTri: Ensemble Learning with Tri-level Representations for Explainable Scene Recognition. CoRR abs/2307.12442 (2023)
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Rui Mao, Guanyi Chen, Xulang Zhang, Frank Guerin, Erik Cambria:
GPTEval: A Survey on Assessments of ChatGPT and GPT-4. CoRR abs/2308.12488 (2023)
[i76]
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Siddique Latif, Moazzam Shoukat, Fahad Shamshad, Muhammad Usama, Yi Ren, Heriberto Cuayáhuitl, Wenwu Wang, Xulong Zhang, Roberto Togneri, Erik Cambria, Björn W. Schuller:
Sparks of Large Audio Models: A Survey and Outlook. CoRR abs/2308.12792 (2023)
[i75]
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  - journals/corr/abs-2308-13911
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Mostafa M. Amin, Rui Mao, Erik Cambria, Björn W. Schuller:
A Wide Evaluation of ChatGPT on Affective Computing Tasks. CoRR abs/2308.13911 (2023)
[i74]
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  - journals/corr/abs-2309-02726
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Zonglin Yang, Xinya Du, Junxian Li, Jie Zheng, Soujanya Poria, Erik Cambria:
Large Language Models for Automated Open-domain Scientific Hypotheses Discovery. CoRR abs/2309.02726 (2023)
[i73]
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  - journals/corr/abs-2309-11960
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Wei Jie Yeo, Wihan van der Heever, Rui Mao, Erik Cambria, Ranjan Satapathy, Gianmarco Mengaldo:
A Comprehensive Review on Financial Explainable AI. CoRR abs/2309.11960 (2023)
[i72]
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  - journals/corr/abs-2310-05694
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Kai He, Rui Mao, Qika Lin, Yucheng Ruan, Xiang Lan, Mengling Feng, Erik Cambria:
A Survey of Large Language Models for Healthcare: from Data, Technology, and Applications to Accountability and Ethics. CoRR abs/2310.05694 (2023)
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Rui Mao, Kai He, Xulang Zhang, Guanyi Chen, Jinjie Ni, Zonglin Yang, Erik Cambria:
A Survey on Semantic Processing Techniques. CoRR abs/2310.18345 (2023)
[i70]
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  - journals/corr/abs-2311-11267
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Shaoxiong Ji, Tianlin Zhang, Kailai Yang, Sophia Ananiadou, Erik Cambria:
Rethinking Large Language Models in Mental Health Applications. CoRR abs/2311.11267 (2023)
2022
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Tahani H. Alwaneen, Aqil M. Azmi, Hatim A. Aboalsamh, Erik Cambria, Amir Hussain:
Arabic question answering system: a survey. Artif. Intell. Rev. 55(1): 207-253 (2022)
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Sahraoui Dhelim, Nyothiri Aung, Mohammed Amine Bouras, Huansheng Ning, Erik Cambria:
A survey on personality-aware recommendation systems. Artif. Intell. Rev. 55(3): 2409-2454 (2022)
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Lorenzo Malandri, Carlos Porcel, Frank Xing, Jesús Serrano-Guerrero, Erik Cambria:
Soft computing for recommender systems and sentiment analysis. Appl. Soft Comput. 118: 108246 (2022)
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Arwa Diwali, Kia Dashtipour, Kawther Saeedi, Mandar Gogate, Erik Cambria, Amir Hussain:
Arabic sentiment analysis using dependency-based rules and deep neural networks. Appl. Soft Comput. 127: 109377 (2022)
[j160]
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Kai He, Rui Mao, Tieliang Gong, Erik Cambria, Chen Li:
JCBIE: a joint continual learning neural network for biomedical information extraction. BMC Bioinform. 23(1): 549 (2022)
[j159]
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Erik Cambria, Amir Hussain:
Guest Editorial: A Decade of Sentic Computing. Cogn. Comput. 14(1): 1-4 (2022)
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Yosephine Susanto, Erik Cambria, Ng Bee Chin, Amir Hussain:
Ten Years of Sentic Computing. Cogn. Comput. 14(1): 5-23 (2022)
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Vibeke Sørensen, J. Stephen Lansing, Nagaraju Thummanapalli, Erik Cambria:
Mood of the Planet: Challenging Visions of Big Data in the Arts. Cogn. Comput. 14(1): 310-321 (2022)
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Abhinaba Roy, Deepanway Ghosal, Erik Cambria, Navonil Majumder, Rada Mihalcea, Soujanya Poria:
Improving Zero-Shot Learning Baselines with Commonsense Knowledge. Cogn. Comput. 14(6): 2212-2222 (2022)
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Shervin Minaee, Nal Kalchbrenner, Erik Cambria, Narjes Nikzad, Meysam Chenaghlu, Jianfeng Gao:
Deep Learning-based Text Classification: A Comprehensive Review. ACM Comput. Surv. 54(3): 62:1-62:40 (2022)
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Mauro Dragoni, Ivan Donadello, Erik Cambria:
OntoSenticNet 2: Enhancing Reasoning Within Sentiment Analysis. IEEE Intell. Syst. 37(2): 103-110 (2022)
[j153]
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Ranjan Satapathy, Shweta Pardeshi, Erik Cambria:
Polarity and Subjectivity Detection with Multitask Learning and BERT Embedding. Future Internet 14(7): 191 (2022)
[j152]
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Wei Li, Wei Shao, Shaoxiong Ji, Erik Cambria:
BiERU: Bidirectional emotional recurrent unit for conversational sentiment analysis. Neurocomputing 467: 73-82 (2022)
[j151]
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Yang Li, Amirmohammad Kazemeini, Yash Mehta, Erik Cambria:
Multitask learning for emotion and personality traits detection. Neurocomputing 493: 340-350 (2022)
[j150]
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Rui Mao, Xiao Li, Mengshi Ge, Erik Cambria:
MetaPro: A computational metaphor processing model for text pre-processing. Inf. Fusion 86-87: 30-43 (2022)
[j149]
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  - journals/isci/KumarTC22
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J. Ashok Kumar, Tina Esther Trueman, Erik Cambria:
Gender-based multi-aspect sentiment detection using multilabel learning. Inf. Sci. 606: 453-468 (2022)
[j148]
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Bin Liang, Hang Su, Lin Gui, Erik Cambria, Ruifeng Xu:
Aspect-based sentiment analysis via affective knowledge enhanced graph convolutional networks. Knowl. Based Syst. 235: 107643 (2022)
[j147]
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Erik Cambria, Akshi Kumar, Mahmoud Al-Ayyoub, Newton Howard:
Guest Editorial: Explainable artificial intelligence for sentiment analysis. Knowl. Based Syst. 238: 107920 (2022)
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Abhinaba Roy, Erik Cambria:
Soft labeling constraint for generalizing from sentiments in single domain. Knowl. Based Syst. 245: 108346 (2022)
[j145]
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Yang Li, Quan Pan, Erik Cambria:
Deep-attack over the deep reinforcement learning. Knowl. Based Syst. 250: 108965 (2022)
[j144]
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Xiaoshi Zhong, Erik Cambria, Amir Hussain:
Does semantics aid syntax? An empirical study on named entity recognition and classification. Neural Comput. Appl. 34(11): 8373-8384 (2022)
[j143]
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Shaoxiong Ji, Xue Li, Zi Huang, Erik Cambria:
Suicidal ideation and mental disorder detection with attentive relation networks. Neural Comput. Appl. 34(13): 10309-10319 (2022)
[j142]
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Vlad Pandelea, Edoardo Ragusa, Tom Young, Paolo Gastaldo, Erik Cambria:
Toward hardware-aware deep-learning-based dialogue systems. Neural Comput. Appl. 34(13): 10397-10408 (2022)
[j141]
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Gourav Bathla, Pardeep Singh, Rahul Kumar Singh, Erik Cambria, Rajeev Tiwari:
Intelligent fake reviews detection based on aspect extraction and analysis using deep learning. Neural Comput. Appl. 34(22): 20213-20229 (2022)
[j140]
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Iti Chaturvedi, Qian Chen, Erik Cambria, Desmond McConnell:
Landmark calibration for facial expressions and fish classification. Signal Image Video Process. 16(2): 377-384 (2022)
[j139]
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Iti Chaturvedi, Qian Chen, Roy E. Welsch, Kishor Thapa, Erik Cambria:
Gaussian correction for adversarial learning of boundaries. Signal Process. Image Commun. 109: 116841 (2022)
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Erik Cambria, Frank Xing, Mike Thelwall, Roy E. Welsch:
Guest Editorial: Sentiment Analysis as a Multidisciplinary Research Area. IEEE Trans. Artif. Intell. 3(5): 638-641 (2022)
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Geng Tu, Jintao Wen, Cheng Liu, Dazhi Jiang, Erik Cambria:
Context- and Sentiment-Aware Networks for Emotion Recognition in Conversation. IEEE Trans. Artif. Intell. 3(5): 699-708 (2022)
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Ke Zhang, Yuanqing Li, Jingyu Wang, Erik Cambria, Xuelong Li:
Real-Time Video Emotion Recognition Based on Reinforcement Learning and Domain Knowledge. IEEE Trans. Circuits Syst. Video Technol. 32(3): 1034-1047 (2022)
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Shaoxiong Ji, Shirui Pan, Erik Cambria, Pekka Marttinen, Philip S. Yu:
A Survey on Knowledge Graphs: Representation, Acquisition, and Applications. IEEE Trans. Neural Networks Learn. Syst. 33(2): 494-514 (2022)
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Mengshi Ge, Rui Mao, Erik Cambria:
Explainable Metaphor Identification Inspired by Conceptual Metaphor Theory. AAAI 2022: 10681-10689
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Jinjie Ni, Vlad Pandelea, Tom Young, Haicang Zhou, Erik Cambria:
HiTKG: Towards Goal-Oriented Conversations via Multi-Hierarchy Learning. AAAI 2022: 11112-11120
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Tom Young, Frank Xing, Vlad Pandelea, Jinjie Ni, Erik Cambria:
Fusing Task-Oriented and Open-Domain Dialogues in Conversational Agents. AAAI 2022: 11622-11629
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Ran Zhou, Xin Li, Ruidan He, Lidong Bing, Erik Cambria, Luo Si, Chunyan Miao:
MELM: Data Augmentation with Masked Entity Language Modeling for Low-Resource NER. ACL (1) 2022: 2251-2262
[c161]
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Sooji Han, Rui Mao, Erik Cambria:
Hierarchical Attention Network for Explainable Depression Detection on Twitter Aided by Metaphor Concept Mappings. COLING 2022: 94-104
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Ran Zhou, Xin Li, Lidong Bing, Erik Cambria, Luo Si, Chunyan Miao:
ConNER: Consistency Training for Cross-lingual Named Entity Recognition. EMNLP 2022: 8438-8449
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Erik Cambria, Rui Mao, Sooji Han, Qian Liu:
Sentic Parser: A Graph-Based Approach to Concept Extraction for Sentiment Analysis. ICDM (Workshops) 2022: 1-8
[c158]
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Anand Choudhary, Erik Cambria:
Making Sense of Sentiments for Aesthetic Plastic Surgery. ICDM (Workshops) 2022: 411-418
[c157]
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Ashok Kumar J, Tina Esther Trueman, Erik Cambria:
Stress Identification in Online Social Networks. ICDM (Workshops) 2022: 427-434
[c156]
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Jayit Saha, Smit Patel, Frank Xing, Erik Cambria:
Does Social Media Sentiment Predict Bitcoin Trading Volume? ICIS 2022
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Cuc Duong, Qian Liu, Rui Mao, Erik Cambria:
Saving Earth One Tweet at a Time through the Lens of Artificial Intelligence. IJCNN 2022: 1-9
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Aryan Rastogi, Qian Liu, Erik Cambria:
Stress Detection from Social Media Articles: New Dataset Benchmark and Analytical Study. IJCNN 2022: 1-8
[c153]
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Erik Cambria, Qian Liu, Sergio Decherchi, Frank Xing, Kenneth Kwok:
SenticNet 7: A Commonsense-based Neurosymbolic AI Framework for Explainable Sentiment Analysis. LREC 2022: 3829-3839
[c152]
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Shaoxiong Ji, Tianlin Zhang, Luna Ansari, Jie Fu, Prayag Tiwari, Erik Cambria:
MentalBERT: Publicly Available Pretrained Language Models for Mental Healthcare. LREC 2022: 7184-7190
[c151]
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  - conf/mm/ChristABTKMSM0C22
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Lukas Christ, Shahin Amiriparian, Alice Baird, Panagiotis Tzirakis, Alexander Kathan, Niklas Müller, Lukas Stappen, Eva-Maria Meßner, Andreas König, Alan Cowen, Erik Cambria, Björn W. Schuller:
The MuSe 2022 Multimodal Sentiment Analysis Challenge: Humor, Emotional Reactions, and Stress. MuSe @ ACM Multimedia 2022: 5-14
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Shahin Amiriparian, Lukas Christ, Andreas König, Eva-Maria Meßner, Alan Cowen, Erik Cambria, Björn W. Schuller:
MuSe 2022 Challenge: Multimodal Humour, Emotional Reactions, and Stress. ACM Multimedia 2022: 7389-7391
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Shahin Amiriparian, Lukas Christ, Andreas König, Alan Cowen, Eva-Maria Meßner, Erik Cambria, Björn W. Schuller:
MuSe@MM 2022: Proceedings of the 3rd International on Multimodal Sentiment Analysis Workshop and Challenge, Lisboa, Portugal, 10 October 2022. ACM 2022, ISBN 978-1-4503-9484-0 [contents]
[i69]
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Ranjan Satapathy, Shweta Pardeshi, Erik Cambria:
Polarity and Subjectivity Detection with Multitask Learning and BERT Embedding. CoRR abs/2201.05363 (2022)
[i68]
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  - journals/corr/abs-2205-00807
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Yang Li, Quan Pan, Erik Cambria:
Deep-Attack over the Deep Reinforcement Learning. CoRR abs/2205.00807 (2022)
[i67]
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Alice Baird, Panagiotis Tzirakis, Gauthier Gidel, Marco Jiralerspong, Eilif B. Muller, Kory W. Mathewson, Björn W. Schuller, Erik Cambria, Dacher Keltner, Alan Cowen:
The ICML 2022 Expressive Vocalizations Workshop and Competition: Recognizing, Generating, and Personalizing Vocal Bursts. CoRR abs/2205.01780 (2022)
[i66]
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  - journals/corr/abs-2207-05691
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Lukas Christ, Shahin Amiriparian, Alice Baird, Panagiotis Tzirakis, Alexander Kathan, Niklas Müller, Lukas Stappen, Eva-Maria Meßner, Andreas König, Alan Cowen, Erik Cambria, Björn W. Schuller:
The MuSe 2022 Multimodal Sentiment Analysis Challenge: Humor, Emotional Reactions, and Stress. CoRR abs/2207.05691 (2022)
[i65]
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  - journals/corr/abs-2207-06958
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Alice Baird, Panagiotis Tzirakis, Gauthier Gidel, Marco Jiralerspong, Eilif B. Muller, Kory W. Mathewson, Björn W. Schuller, Erik Cambria, Dacher Keltner, Alan Cowen:
Proceedings of the ICML 2022 Expressive Vocalizations Workshop and Competition: Recognizing, Generating, and Personalizing Vocal Bursts. CoRR abs/2207.06958 (2022)
[i64]
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  - journals/corr/abs-2209-07494
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Sooji Han, Rui Mao, Erik Cambria:
Hierarchical Attention Network for Explainable Depression Detection on Twitter Aided by Metaphor Concept Mappings. CoRR abs/2209.07494 (2022)
[i63]
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  - journals/corr/abs-2210-08994
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Seng-Beng Ho, Zhaoxia Wang, Boon-Kiat Quek, Erik Cambria:
Knowledge Representation for Conceptual, Motivational, and Affective Processes in Natural Language Communication. CoRR abs/2210.08994 (2022)
[i62]
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Ran Zhou, Xin Li, Lidong Bing, Erik Cambria, Luo Si, Chunyan Miao:
ConNER: Consistency Training for Cross-lingual Named Entity Recognition. CoRR abs/2211.09394 (2022)
[i61]
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  - journals/corr/abs-2212-10923
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Zonglin Yang, Li Dong, Xinya Du, Hao Cheng, Erik Cambria, Xiaodong Liu, Jianfeng Gao, Furu Wei:
Language Models as Inductive Reasoners. CoRR abs/2212.10923 (2022)
2021
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Yong Shi, Wei Li, Luyao Zhu, Kun Guo, Erik Cambria:
Stock trading rule discovery with double deep Q-network. Appl. Soft Comput. 107: 107320 (2021)
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Ashok Kumar J, Tina Esther Trueman, Erik Cambria:
A Convolutional Stacked Bidirectional LSTM with a Multiplicative Attention Mechanism for Aspect Category and Sentiment Detection. Cogn. Comput. 13(6): 1423-1432 (2021)
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Qingnan Jiang, Lei Chen, Wei Zhao, Min Yang, Erik Cambria:
Toward Aspect-Level Sentiment Modification Without Parallel Data. IEEE Intell. Syst. 36(1): 75-81 (2021)
[j131]
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Lukas Stappen, Alice Baird, Erik Cambria, Björn W. Schuller:
Sentiment Analysis and Topic Recognition in Video Transcriptions. IEEE Intell. Syst. 36(2): 88-95 (2021)
[j130]
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Wei Peng, Xiaopeng Hong, Guoying Zhao, Erik Cambria:
Adaptive Modality Distillation for Separable Multimodal Sentiment Analysis. IEEE Intell. Syst. 36(3): 82-89 (2021)
[j129]
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Mike Thelwall, Erik Cambria:
This! Identifying New Sentiment Slang Through Orthographic Pleonasm Online: Yasss Slay Gorg Queen Ilysm. IEEE Intell. Syst. 36(4): 114-120 (2021)
[j128]
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Raymond Chiong, Gregorious Satia Budhi, Sandeep Dhakal, Erik Cambria:
Combining Sentiment Lexicons and Content-Based Features for Depression Detection. IEEE Intell. Syst. 36(6): 99-105 (2021)
[j127]
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Mohammad Ehsan Basiri, Shahla Nemati, Moloud Abdar, Erik Cambria, U. Rajendra Acharya:
ABCDM: An Attention-based Bidirectional CNN-RNN Deep Model for sentiment analysis. Future Gener. Comput. Syst. 115: 279-294 (2021)
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Ashok Kumar J, S. Abiramy, Tina Esther Trueman, Erik Cambria:
Comment toxicity detection via a multichannel convolutional bidirectional gated recurrent unit. Neurocomputing 441: 272-278 (2021)
[j125]
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Kia Dashtipour, Mandar Gogate, Erik Cambria, Amir Hussain:
A novel context-aware multimodal framework for persian sentiment analysis. Neurocomputing 457: 377-388 (2021)
[j124]
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Erik Cambria, Shaoxiong Ji, Shirui Pan, Philip S. Yu:
Knowledge graph representation and reasoning. Neurocomputing 461: 494-496 (2021)
[j123]
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Iti Chaturvedi, Kishor Thapa, Sandro Cavallari, Erik Cambria, Roy E. Welsch:
Predicting video engagement using heterogeneous DeepWalk. Neurocomputing 465: 228-237 (2021)
[j122]
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Haiyun Peng, Yukun Ma, Soujanya Poria, Yang Li, Erik Cambria:
Phonetic-enriched text representation for Chinese sentiment analysis with reinforcement learning. Inf. Fusion 70: 88-99 (2021)
[j121]
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Amir Hussain, Erik Cambria, Soujanya Poria, Ahmad Y. A. Hawalah, Francisco Herrera:
Information fusion for affective computing and sentiment analysis. Inf. Fusion 71: 97-98 (2021)
[j120]
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Wei Li, Luyao Zhu, Erik Cambria:
Taylor's theorem: A new perspective for neural tensor networks. Knowl. Based Syst. 228: 107258 (2021)
[j119]
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Yang Li, Wei Zhao, Erik Cambria, Suhang Wang, Steffen Eger:
Graph routing between capsules. Neural Networks 143: 345-354 (2021)
[j118]
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Qian Chen, Iti Chaturvedi, Shaoxiong Ji, Erik Cambria:
Sequential fusion of facial appearance and dynamics for depression recognition. Pattern Recognit. Lett. 150: 115-121 (2021)
[j117]
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Vlad Pandelea, Edoardo Ragusa, Tommaso Apicella, Paolo Gastaldo, Erik Cambria:
Emotion Recognition on Edge Devices: Training and Deployment. Sensors 21(13): 4496 (2021)
[j116]
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Shaoxiong Ji, Shirui Pan, Xue Li, Erik Cambria, Guodong Long, Zi Huang:
Suicidal Ideation Detection: A Review of Machine Learning Methods and Applications. IEEE Trans. Comput. Soc. Syst. 8(1): 214-226 (2021)
[j115]
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Francesco Piccialli, Nik Bessis, Erik Cambria:
Guest Editorial: Industrial Internet of Things: Where Are We and What Is Next? IEEE Trans. Ind. Informatics 17(11): 7700-7703 (2021)
[c149]
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Snehameena Arumugam, Likai Peng, Jin-Cheon Na, Guangze Lin, Roopika Ganesh, Xiaoyin Li, Qing Chen, Shirley S. Ho, Erik Cambria:
A Prototype System for Monitoring Emotion and Sentiment Trends Towards Nuclear Energy on Twitter Using Deep Learning. ICADL 2021: 471-479
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Dazhi Jiang, Runguo Wei, Hao Liu, Jintao Wen, Geng Tu, Lin Zheng, Erik Cambria:
A Multitask Learning Framework for Multimodal Sentiment Analysis. ICDM (Workshops) 2021: 151-157
[c147]
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Amirmohammad Kazemeini, Sudipta Singha Roy, Robert E. Mercer, Erik Cambria:
Interpretable Representation Learning for Personality Detection. ICDM (Workshops) 2021: 158-165
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Ashok Kumar J, Erik Cambria, Tina Esther Trueman:
DUSE: A New Benchmark Dataset for Drug User Sentiment Extraction. ICDM (Workshops) 2021: 174-178
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Lukas Stappen, Alice Baird, Lukas Christ, Lea Schumann, Benjamin Sertolli, Eva-Maria Meßner, Erik Cambria, Guoying Zhao, Björn W. Schuller:
The MuSe 2021 Multimodal Sentiment Analysis Challenge: Sentiment, Emotion, Physiological-Emotion, and Stress. MuSe @ ACM Multimedia 2021: 5-14
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Lukas Stappen, Lea Schumann, Benjamin Sertolli, Alice Baird, Benjamin Weigel, Erik Cambria, Björn W. Schuller:
MuSe-Toolbox: The Multimodal Sentiment Analysis Continuous Annotation Fusion and Discrete Class Transformation Toolbox. MuSe @ ACM Multimedia 2021: 75-82
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Lukas Stappen, Eva-Maria Meßner, Erik Cambria, Guoying Zhao, Björn W. Schuller:
MuSe 2021 Challenge: Multimodal Emotion, Sentiment, Physiological-Emotion, and Stress Detection. ACM Multimedia 2021: 5706-5707
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Wei Sun, Shaoxiong Ji, Erik Cambria, Pekka Marttinen:
Multitask Recalibrated Aggregation Network for Medical Code Prediction. ECML/PKDD (4) 2021: 367-383
[c141]
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Ashok Kumar J, Erik Cambria, Tina Esther Trueman:
Transformer-Based Bidirectional Encoder Representations for Emotion Detection from Text. SSCI 2021: 1-6
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Björn W. Schuller, Lukas Stappen, Eva-Maria Meßner, Erik Cambria, Guoying Zhao:
MuSe '21: Proceedings of the 2nd on Multimodal Sentiment Analysis Challenge, Virtual Event, China, 24 October 2021. ACM 2021, ISBN 978-1-4503-8678-4 [contents]
[i60]
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Siddique Latif, Heriberto Cuayáhuitl, Farrukh Pervez, Fahad Shamshad, Hafiz Shehbaz Ali, Erik Cambria:
A Survey on Deep Reinforcement Learning for Audio-Based Applications. CoRR abs/2101.00240 (2021)
[i59]
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Yang Li, Amirmohammad Kazameini, Yash Mehta, Erik Cambria:
Multitask Learning for Emotion and Personality Detection. CoRR abs/2101.02346 (2021)
[i58]
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Sahraoui Dhelim, Nyothiri Aung, Mohammed Amine Bouras, Huansheng Ning, Erik Cambria:
A Survey on Personality-Aware Recommendation Systems. CoRR abs/2101.12153 (2021)
[i57]
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Kia Dashtipour, Mandar Gogate, Erik Cambria, Amir Hussain:
A Novel Context-Aware Multimodal Framework for Persian Sentiment Analysis. CoRR abs/2103.02636 (2021)
[i56]
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Wei Sun, Shaoxiong Ji, Erik Cambria, Pekka Marttinen:
Multitask Recalibrated Aggregation Network for Medical Code Prediction. CoRR abs/2104.00952 (2021)
[i55]
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Lukas Stappen, Alice Baird, Lukas Christ, Lea Schumann, Benjamin Sertolli, Eva-Maria Messner, Erik Cambria, Guoying Zhao, Björn W. Schuller:
The MuSe 2021 Multimodal Sentiment Analysis Challenge: Sentiment, Emotion, Physiological-Emotion, and Stress. CoRR abs/2104.07123 (2021)
[i54]
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  - journals/corr/abs-2105-01331
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Hasan Kemik, Nusret Özates, Meysam Asgari-Chenaghlu, Erik Cambria:
BLM-17m: A Large-Scale Dataset for Black Lives Matter Topic Detection on Twitter. CoRR abs/2105.01331 (2021)
[i53]
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Jinjie Ni, Tom Young, Vlad Pandelea, Fuzhao Xue, Vinay Adiga, Erik Cambria:
Recent Advances in Deep Learning Based Dialogue Systems: A Systematic Survey. CoRR abs/2105.04387 (2021)
[i52]
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Ng Bee Chin, Yosephine Susanto, Erik Cambria:
MICE: A Crosslinguistic Emotion Corpus in Malay, Indonesian, Chinese and English. CoRR abs/2106.04831 (2021)
[i51]
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Yang Li, Wei Zhao, Erik Cambria, Suhang Wang, Steffen Eger:
Graph Routing between Capsules. CoRR abs/2106.11531 (2021)
[i50]
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Lukas Stappen, Lea Schumann, Benjamin Sertolli, Alice Baird, Benjamin Weigel, Erik Cambria, Björn W. Schuller:
MuSe-Toolbox: The Multimodal Sentiment Analysis Continuous Annotation Fusion and Discrete Class Transformation Toolbox. CoRR abs/2107.11757 (2021)
[i49]
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  - journals/corr/abs-2108-13655
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Ran Zhou, Ruidan He, Xin Li, Lidong Bing, Erik Cambria, Luo Si, Chunyan Miao:
MELM: Data Augmentation with Masked Entity Language Modeling for Cross-lingual NER. CoRR abs/2108.13655 (2021)
[i48]
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  - journals/corr/abs-2109-02418
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Wei Sun, Shaoxiong Ji, Erik Cambria, Pekka Marttinen:
Multi-task Balanced and Recalibrated Network for Medical Code Prediction. CoRR abs/2109.02418 (2021)
[i47]
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Tom Young, Frank Z. Xing, Vlad Pandelea, Jinjie Ni, Erik Cambria:
Fusing task-oriented and open-domain dialogues in conversational agents. CoRR abs/2109.04137 (2021)
[i46]
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  - journals/corr/abs-2110-15621
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Shaoxiong Ji, Tianlin Zhang, Luna Ansari, Jie Fu, Prayag Tiwari, Erik Cambria:
MentalBERT: Publicly Available Pretrained Language Models for Mental Healthcare. CoRR abs/2110.15621 (2021)
2020
[j114]
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Yash Mehta, Navonil Majumder, Alexander F. Gelbukh, Erik Cambria:
Recent trends in deep learning based personality detection. Artif. Intell. Rev. 53(4): 2313-2339 (2020)
[j113]
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Wei Li, Luyao Zhu, Yong Shi, Kun Guo, Erik Cambria:
User reviews: Sentiment analysis using lexicon integrated two-channel CNN-LSTM family models. Appl. Soft Comput. 94: 106435 (2020)
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Aparup Khatua, Apalak Khatua, Erik Cambria:
Predicting political sentiments of voters from Twitter in multi-party contexts. Appl. Soft Comput. 97(Part): 106743 (2020)
[j111]
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Md. Shad Akhtar, Asif Ekbal, Erik Cambria:
How Intense Are You? Predicting Intensities of Emotions and Sentiments using Stacked Ensemble [Application Notes]. IEEE Comput. Intell. Mag. 15(1): 64-75 (2020)
[j110]
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Cecilio Angulo, Zoe Falomir, Davide Anguita, Núria Agell, Erik Cambria:
Bridging Cognitive Models and Recommender Systems. Cogn. Comput. 12(2): 426-427 (2020)
[j109]
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Ranjan Satapathy, Erik Cambria, Andrea Nanetti, Amir Hussain:
A Review of Shorthand Systems: From Brachygraphy to Microtext and Beyond. Cogn. Comput. 12(4): 778-792 (2020)
[j108]
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Xiaoshi Zhong, Erik Cambria, Amir Hussain:
Extracting Time Expressions and Named Entities with Constituent-Based Tagging Schemes. Cogn. Comput. 12(4): 844-862 (2020)
[j107]
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Jetze Schuurmans, Flavius Frasincar, Erik Cambria:
Intent Classification for Dialogue Utterances. IEEE Intell. Syst. 35(1): 82-88 (2020)
[j106]
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Jian-Wu Bi, Yang Liu, Zhi-Ping Fan, Erik Cambria:
Crowd Intelligence: Conducting Asymmetric Impact-Performance Analysis Based on Online Reviews. IEEE Intell. Syst. 35(2): 92-98 (2020)
[j105]
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Jiachen Du, Lin Gui, Ruifeng Xu, Yunqing Xia, Xuan Wang, Erik Cambria:
Commonsense Knowledge Enhanced Memory Network for Stance Classification. IEEE Intell. Syst. 35(4): 102-109 (2020)
[j104]
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Yosephine Susanto, Andrew G. Livingstone, Ng Bee Chin, Erik Cambria:
The Hourglass Model Revisited. IEEE Intell. Syst. 35(5): 96-102 (2020)
[j103]
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  - journals/fgcs/OueslatiCHO20
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Oumaima Oueslati, Erik Cambria, Moez Ben HajHmida, Habib Ounelli:
A review of sentiment analysis research in Arabic language. Future Gener. Comput. Syst. 112: 408-430 (2020)
[j102]
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Tom Young, Vlad Pandelea, Soujanya Poria, Erik Cambria:
Dialogue systems with audio context. Neurocomputing 388: 102-109 (2020)
[j101]
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Edoardo Ragusa, Paolo Gastaldo, Rodolfo Zunino, Erik Cambria:
Balancing computational complexity and generalization ability: A novel design for ELM. Neurocomputing 401: 405-417 (2020)
[j100]
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Yang Li, Suhang Wang, Yukun Ma, Quan Pan, Erik Cambria:
Popularity prediction on vacation rental websites. Neurocomputing 412: 372-380 (2020)
[j99]
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Zhaoxia Wang, Seng-Beng Ho, Erik Cambria:
Multi-Level Fine-Scaled Sentiment Sensing with Ambivalence Handling. Int. J. Uncertain. Fuzziness Knowl. Based Syst. 28(4): 683-697 (2020)
[j98]
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Rhea Sukthanker, Soujanya Poria, Erik Cambria, Ramkumar Thirunavukarasu:
Anaphora and coreference resolution: A review. Inf. Fusion 59: 139-162 (2020)
[j97]
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David Camacho, Ángel Panizo-LLedot, Gema Bello Orgaz, Antonio González-Pardo, Erik Cambria:
The four dimensions of social network analysis: An overview of research methods, applications, and software tools. Inf. Fusion 63: 88-120 (2020)
[j96]
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Yukun Ma, Khanh Linh Nguyen, Frank Z. Xing, Erik Cambria:
A survey on empathetic dialogue systems. Inf. Fusion 64: 50-70 (2020)
[j95]
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Frank Z. Xing, Soujanya Poria, Erik Cambria, Roy E. Welsch:
Social Media Marketing and Financial Forecasting. Inf. Process. Manag. 57(5): 102314 (2020)
[j94]
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Ana Valdivia, Eugenio Martínez-Cámara, Iti Chaturvedi, María Victoria Luzón, Erik Cambria, Yew-Soon Ong, Francisco Herrera:
What do people think about this monument? Understanding negative reviews via deep learning, clustering and descriptive rules. J. Ambient Intell. Humaniz. Comput. 11(1): 39-52 (2020)
[j93]
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Zhaoxia Wang, Seng-Beng Ho, Erik Cambria:
A review of emotion sensing: categorization models and algorithms. Multim. Tools Appl. 79(47): 35553-35582 (2020)
[j92]
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Haotian Xu, Haiyun Peng, Haoran Xie, Erik Cambria, Liuyang Zhou, Weiguo Zheng:
End-to-End latent-variable task-oriented dialogue system with exact log-likelihood optimization. World Wide Web 23(3): 1989-2002 (2020)
[c140]
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Shaoxiong Ji, Erik Cambria, Pekka Marttinen:
Dilated Convolutional Attention Network for Medical Code Assignment from Clinical Text. ClinicalNLP@EMNLP 2020: 73-78
[c139]
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Iti Chaturvedi, Erik Cambria, Sandro Cavallari, Roy E. Welsch:
Genetic Programming for Domain Adaptation in Product Reviews. CEC 2020: 1-8
[c138]
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Erik Cambria, Yang Li, Frank Z. Xing, Soujanya Poria, Kenneth Kwok:
SenticNet 6: Ensemble Application of Symbolic and Subsymbolic AI for Sentiment Analysis. CIKM 2020: 105-114
[c137]
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Frank Z. Xing, Lorenzo Malandri, Yue Zhang, Erik Cambria:
Financial Sentiment Analysis: An Investigation into Common Mistakes and Silver Bullets. COLING 2020: 978-987
[c136]
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Jonathan Kevin Chandra, Erik Cambria, Andrea Nanetti:
One Belt, One Road, One Sentiment? A Hybrid Approach to Gauging Public Opinions on the New Silk Road Initiative. ICDM (Workshops) 2020: 7-14
[c135]
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Iti Chaturvedi, Edoardo Ragusa, Paolo Gastaldo, Erik Cambria:
COAL: Convolutional Online Adaptation Learning for Opinion Mining. ICDM (Workshops) 2020: 15-22
[c134]
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Yash Mehta, Samin Fatehi, Amirmohammad Kazameini, Clemens Stachl, Erik Cambria, Sauleh Eetemadi:
Bottom-Up and Top-Down: Predicting Personality with Psycholinguistic and Language Model Features. ICDM 2020: 1184-1189
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Claudia Guerreiro, Erik Cambria, Hien T. Nguyen:
New Avenues in Mobile Tourism. IJCNN 2020: 1-8
[c132]
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  - conf/ijcnn/KhatuaCHN20
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Aparup Khatua, Erik Cambria, Shirley S. Ho, Jin-Cheon Na:
Deciphering Public Opinion of Nuclear Energy on Twitter. IJCNN 2020: 1-8
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  - conf/mm/StappenBRTDHSMS20
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Lukas Stappen, Alice Baird, Georgios Rizos, Panagiotis Tzirakis, Xinchen Du, Felix Hafner, Lea Schumann, Adria Mallol-Ragolta, Björn W. Schuller, Iulia Lefter, Erik Cambria, Ioannis Kompatsiaris:
MuSe 2020 Challenge and Workshop: Multimodal Sentiment Analysis, Emotion-target Engagement and Trustworthiness Detection in Real-life Media: Emotional Car Reviews in-the-wild. MuSe @ ACM Multimedia 2020: 35-44
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Lukas Stappen, Björn W. Schuller, Iulia Lefter, Erik Cambria, Ioannis Kompatsiaris:
Summary of MuSe 2020: Multimodal Sentiment Analysis, Emotion-target Engagement and Trustworthiness Detection in Real-life Media. ACM Multimedia 2020: 4769-4770
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  - conf/semeval/FadelAC20
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Ali Fadel, Mahmoud Al-Ayyoub, Erik Cambria:
JUSTers at SemEval-2020 Task 4: Evaluating Transformer Models against Commonsense Validation and Explanation. SemEval@COLING 2020: 535-542
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Björn W. Schuller, Iulia Lefter, Erik Cambria, Ioannis Kompatsiaris, Lukas Stappen:
MuSe'20: Proceedings of the 1st International on Multimodal Sentiment Analysis in Real-life Media Challenge and Workshop, Seattle, WA, USA, October 16, 2020. ACM 2020, ISBN 978-1-4503-8157-4 [contents]
[i45]
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  - journals/corr/abs-2002-00388
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Shaoxiong Ji, Shirui Pan, Erik Cambria, Pekka Marttinen, Philip S. Yu:
A Survey on Knowledge Graphs: Representation, Acquisition and Applications. CoRR abs/2002.00388 (2020)
[i44]
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  - journals/corr/abs-2002-09485
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David Camacho, Ángel Panizo-LLedot, Gema Bello Orgaz, Antonio González-Pardo, Erik Cambria:
The Four Dimensions of Social Network Analysis: An Overview of Research Methods, Applications, and Software Tools. CoRR abs/2002.09485 (2020)
[i43]
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  - journals/corr/abs-2004-03705
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Shervin Minaee, Nal Kalchbrenner, Erik Cambria, Narjes Nikzad, Meysam Chenaghlu, Jianfeng Gao:
Deep Learning Based Text Classification: A Comprehensive Review. CoRR abs/2004.03705 (2020)
[i42]
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  - journals/corr/abs-2004-07601
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Shaoxiong Ji, Xue Li, Zi Huang, Erik Cambria:
Suicidal Ideation and Mental Disorder Detection with Attentive Relation Networks. CoRR abs/2004.07601 (2020)
[i41]
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  - journals/corr/abs-2004-14858
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Lukas Stappen, Alice Baird, Georgios Rizos, Panagiotis Tzirakis, Xinchen Du, Felix Hafner, Lea Schumann, Adria Mallol-Ragolta, Björn W. Schuller, Iulia Lefter, Erik Cambria, Ioannis Kompatsiaris:
MuSe 2020 - The First International Multimodal Sentiment Analysis in Real-life Media Challenge and Workshop. CoRR abs/2004.14858 (2020)
[i40]
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  - journals/corr/abs-2005-12240
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Oumaima Oueslati, Erik Cambria, Moez Ben HajHmida, Habib Ounelli:
A review of sentiment analysis research in Arabic language. CoRR abs/2005.12240 (2020)
[i39]
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  - journals/corr/abs-2006-00492
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Wei Li, Wei Shao, Shaoxiong Ji, Erik Cambria:
BiERU: Bidirectional Emotional Recurrent Unit for Conversational Sentiment Analysis. CoRR abs/2006.00492 (2020)
[i38]
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  - journals/corr/abs-2009-14578
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Shaoxiong Ji, Erik Cambria, Pekka Marttinen:
Dilated Convolutional Attention Network for Medical Code Assignment from Clinical Text. CoRR abs/2009.14578 (2020)
[i37]
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  - journals/corr/abs-2010-01309
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Amirmohammad Kazameini, Samin Fatehi, Yash Mehta, Sauleh Eetemadi, Erik Cambria:
Personality Trait Detection Using Bagged SVM over BERT Word Embedding Ensembles. CoRR abs/2010.01309 (2020)
[i36]
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  - journals/corr/abs-2012-06236
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Abhinaba Roy, Deepanway Ghosal, Erik Cambria, Navonil Majumder, Rada Mihalcea, Soujanya Poria:
Improving Zero Shot Learning Baselines with Commonsense Knowledge. CoRR abs/2012.06236 (2020)

2010 – 2019

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What is the meaning of the colors in the publication lists?

2019
[j91]
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Erik Cambria, Soujanya Poria, Amir Hussain, Bing Liu:
Computational Intelligence for Affective Computing and Sentiment Analysis [Guest Editorial]. IEEE Comput. Intell. Mag. 14(2): 16-17 (2019)
[j90]
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Sandro Cavallari, Erik Cambria, Hongyun Cai, Kevin Chen-Chuan Chang, Vincent W. Zheng:
Embedding Both Finite and Infinite Communities on Graphs [Application Notes]. IEEE Comput. Intell. Mag. 14(3): 39-50 (2019)
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  - journals/cogcom/RagusaGZC19
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Edoardo Ragusa, Paolo Gastaldo, Rodolfo Zunino, Erik Cambria:
Learning with Similarity Functions: a Tensor-Based Framework. Cogn. Comput. 11(1): 31-49 (2019)
[j88]
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  - journals/eswa/RattoMMOC19
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Andrea Picasso Ratto, Simone Merello, Yukun Ma, Luca Oneto, Erik Cambria:
Technical analysis and sentiment embeddings for market trend prediction. Expert Syst. Appl. 135: 60-70 (2019)
[j87]
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  - journals/expert/ReisCMVBC19
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Julio C. S. Reis, André Correia, Fabricio Murai, Adriano Veloso, Fabrício Benevenuto, Erik Cambria:
Supervised Learning for Fake News Detection. IEEE Intell. Syst. 34(2): 76-81 (2019)
[j86]
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  - journals/expert/MajumderPPCCGC19
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Navonil Majumder, Soujanya Poria, Haiyun Peng, Niyati Chhaya, Erik Cambria, Alexander F. Gelbukh:
Sentiment and Sarcasm Classification With Multitask Learning. IEEE Intell. Syst. 34(3): 38-43 (2019)
[j85]
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  - journals/expert/WelchPKMC19
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Charles Welch, Verónica Pérez-Rosas, Jonathan K. Kummerfeld, Rada Mihalcea, Erik Cambria:
Learning From Personal Longitudinal Dialog Data. IEEE Intell. Syst. 34(4): 16-23 (2019)
[j84]
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  - journals/expert/BukerRVC19
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Abeer A. N. Buker, Giorgio Roffo, Alessandro Vinciarelli, Erik Cambria:
Type Like a Man! Inferring Gender from Keystroke Dynamics in Live-Chats. IEEE Intell. Syst. 34(6): 53-59 (2019)
[j83]
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  - journals/ijon/ValdiviaHCLTCH19
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Ana Valdivia, Emiliya Hrabova, Iti Chaturvedi, María Victoria Luzón, Luigi Troiano, Erik Cambria, Francisco Herrera:
Inconsistencies on TripAdvisor reviews: A unified index between users and Sentiment Analysis Methods. Neurocomputing 353: 3-16 (2019)
[j82]
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  - journals/ijpr/BiLFC19
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Jian-Wu Bi, Yang Liu, Zhi-Ping Fan, Erik Cambria:
Modelling customer satisfaction from online reviews using ensemble neural network and effect-based Kano model. Int. J. Prod. Res. 57(22): 7068-7088 (2019)
[j81]
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  - journals/ipm/KhatuaKC19
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Aparup Khatua, Apalak Khatua, Erik Cambria:
A tale of two epidemics: Contextual Word2Vec for classifying twitter streams during outbreaks. Inf. Process. Manag. 56(1): 247-257 (2019)
[j80]
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Frank Z. Xing, Filippo Pallucchini, Erik Cambria:
Cognitive-inspired domain adaptation of sentiment lexicons. Inf. Process. Manag. 56(3): 554-564 (2019)
[j79]
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  - journals/isci/LiPWPYC19
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Yang Li, Quan Pan, Suhang Wang, Haiyun Peng, Tao Yang, Erik Cambria:
Disentangled Variational Auto-Encoder for semi-supervised learning. Inf. Sci. 482: 73-85 (2019)
[j78]
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  - journals/kbs/XingCW19
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Frank Z. Xing, Erik Cambria, Roy E. Welsch:
Growing semantic vines for robust asset allocation. Knowl. Based Syst. 165: 297-305 (2019)
[j77]
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  - journals/kbs/LiWPPYC19
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Yang Li, Suhang Wang, Quan Pan, Haiyun Peng, Tao Yang, Erik Cambria:
Learning binary codes with neural collaborative filtering for efficient recommendation systems. Knowl. Based Syst. 172: 64-75 (2019)
[j76]
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  - journals/kbs/XingCZ19
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Frank Z. Xing, Erik Cambria, Yue Zhang:
Sentiment-aware volatility forecasting. Knowl. Based Syst. 176: 68-76 (2019)
[j75]
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  - journals/kbs/NguyenDC19
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Hien T. Nguyen, Phuc H. Duong, Erik Cambria:
Learning short-text semantic similarity with word embeddings and external knowledge sources. Knowl. Based Syst. 182 (2019)
[j74]
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  - journals/prl/ChaturvediSCC19
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Iti Chaturvedi, Ranjan Satapathy, Sandro Cavallari, Erik Cambria:
Fuzzy commonsense reasoning for multimodal sentiment analysis. Pattern Recognit. Lett. 125: 264-270 (2019)
[c128]
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  - conf/aaai/MajumderPHMGC19
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Navonil Majumder, Soujanya Poria, Devamanyu Hazarika, Rada Mihalcea, Alexander F. Gelbukh, Erik Cambria:
DialogueRNN: An Attentive RNN for Emotion Detection in Conversations. AAAI 2019: 6818-6825
[c127]
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  - conf/acl/PoriaHMNCM19
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Soujanya Poria, Devamanyu Hazarika, Navonil Majumder, Gautam Naik, Erik Cambria, Rada Mihalcea:
MELD: A Multimodal Multi-Party Dataset for Emotion Recognition in Conversations. ACL (1) 2019: 527-536
[c126]
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  - conf/acl/ZhaoPECY19
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Wei Zhao, Haiyun Peng, Steffen Eger, Erik Cambria, Min Yang:
Towards Scalable and Reliable Capsule Networks for Challenging NLP Applications. ACL (1) 2019: 1549-1559
[c125]
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  - conf/bics/DashtipourRGZCH19
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Kia Dashtipour, Ali Raza, Alexander F. Gelbukh, Rui Zhang, Erik Cambria, Amir Hussain:
PerSent 2.0: Persian Sentiment Lexicon Enriched with Domain-Specific Words. BICS 2019: 497-509
[c124]
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Haiyun Peng, Soujanya Poria, Yang Li, Erik Cambria:
Fusing Phonetic Features and Chinese Character Representation for Sentiment Analysis. CICLing (2) 2019: 151-165
[c123]
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Oumayma Oueslati, Moez Ben Haj Hmida, Habib Ounelli, Erik Cambria:
Sentiment Analysis of Influential Messages for Political Election Forecasting. CICLing (2) 2019: 280-292
[c122]
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Ranjan Satapathy, Erik Cambria, Nadia Magnenat-Thalmann:
Microtext Normalization for Chatbots. CICLing (1) 2019: 293-303
[c121]
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  - conf/comad/KhatuaCGCK19
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Aparup Khatua, Erik Cambria, Kuntal Ghosh, Nabendu Chaki, Apalak Khatua:
Tweeting in Support of LGBT?: A Deep Learning Approach. COMAD/CODS 2019: 342-345
[c120]
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Ranjan Satapathy, Aalind Singh, Erik Cambria:
PhonSenticNet: A Cognitive Approach to Microtext Normalization for Concept-Level Sentiment Analysis. CSoNet 2019: 177-188
[c119]
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  - conf/fuzzIEEE/KhanesarHCK19
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Mojtaba Ahmadieh Khanesar, Saima Hassan, Erik Cambria, Erdal Kayacan:
A Novel Non-Iterative Parameter Estimation Method for Interval Type-2 Fuzzy Neural Networks Based on a Dynamic Cost Function. FUZZ-IEEE 2019: 1-6
[c118]
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Claudia Guerreiro, Erik Cambria, Hien T. Nguyen:
Understanding the Role of Social Media in Backpacker Tourism. ICDM Workshops 2019: 530-537
[c117]
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Sandro Cavallari, Soujanya Poria, Erik Cambria, Vincent W. Zheng, Hongyun Cai:
An Attention-Based Model for Learning Dynamic Interaction Networks. IJCNN 2019: 1-8
[c116]
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  - conf/ijcnn/MerelloROC19
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Simone Merello, Andrea Picasso Ratto, Luca Oneto, Erik Cambria:
Ensemble Application of Transfer Learning and Sample Weighting for Stock Market Prediction. IJCNN 2019: 1-8
[c115]
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Ranjan Satapathy, Yang Li, Sandro Cavallari, Erik Cambria:
Seq2Seq Deep Learning Models for Microtext Normalization. IJCNN 2019: 1-8
[c114]
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  - conf/inns/MerelloROC19
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Simone Merello, Andrea Picasso Ratto, Luca Oneto, Erik Cambria:
Predicting Future Market Trends: Which Is the Optimal Window? INNSBDDL 2019: 180-185
[c113]
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  - conf/ro-man/MishraRSCM19
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Nidhi Mishra, Manoj Ramanathan, Ranjan Satapathy, Erik Cambria, Nadia Magnenat-Thalmann:
Can a Humanoid Robot be part of the Organizational Workforce? A User Study Leveraging Sentiment Analysis. RO-MAN 2019: 1-7
[i35]
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  - journals/corr/abs-1901-07880
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Haiyun Peng, Yukun Ma, Soujanya Poria, Yang Li, Erik Cambria:
Phonetic-enriched Text Representation for Chinese Sentiment Analysis with Reinforcement Learning. CoRR abs/1901.07880 (2019)
[i34]
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  - journals/corr/abs-1901-08014
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Navonil Majumder, Soujanya Poria, Haiyun Peng, Niyati Chhaya, Erik Cambria, Alexander F. Gelbukh:
Sentiment and Sarcasm Classification with Multitask Learning. CoRR abs/1901.08014 (2019)
[i33]
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  - journals/corr/abs-1902-08342
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Rajiv Bajpai, Devamanyu Hazarika, Kunal Singh, Sruthi Gorantla, Erik Cambria, Roger Zimmermann:
Aspect-Sentiment Embeddings for Company Profiling and Employee Opinion Mining. CoRR abs/1902.08342 (2019)
[i32]
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Mimansa Jaiswal, Sairam Tabibu, Erik Cambria:
"Hang in There": Lexical and Visual Analysis to Identify Posts Warranting Empathetic Responses. CoRR abs/1903.05210 (2019)
[i31]
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Ranjan Satapathy, Aalind Singh, Erik Cambria:
PhonSenticNet: A Cognitive Approach to Microtext Normalization for Concept-Level Sentiment Analysis. CoRR abs/1905.01967 (2019)
[i30]
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Nidhi Mishra, Manoj Ramanathan, Ranjan Satapathy, Erik Cambria, Nadia Magnenat-Thalmann:
Can a Humanoid Robot be part of the Organizational Workforce? A User Study Leveraging Sentiment Analysis. CoRR abs/1905.08937 (2019)
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  - journals/corr/abs-1906-02829
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Wei Zhao, Haiyun Peng, Steffen Eger, Erik Cambria, Min Yang:
Towards Scalable and Reliable Capsule Networks for Challenging NLP Applications. CoRR abs/1906.02829 (2019)
[i28]
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Haodong Bai, Frank Z. Xing, Erik Cambria, Win-Bin Huang:
Business Taxonomy Construction Using Concept-Level Hierarchical Clustering. CoRR abs/1906.09694 (2019)
[i27]
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Yash Mehta, Navonil Majumder, Alexander F. Gelbukh, Erik Cambria:
Recent Trends in Deep Learning Based Personality Detection. CoRR abs/1908.03628 (2019)
[i26]
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Shaoxiong Ji, Shirui Pan, Xue Li, Erik Cambria, Guodong Long, Zi Huang:
Suicidal Ideation Detection: A Review of Machine Learning Methods and Applications. CoRR abs/1910.12611 (2019)
2018
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Frank Z. Xing, Erik Cambria, Roy E. Welsch:
Natural language based financial forecasting: a survey. Artif. Intell. Rev. 50(1): 49-73 (2018)
[j72]
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Tom Young, Devamanyu Hazarika, Soujanya Poria, Erik Cambria:
Recent Trends in Deep Learning Based Natural Language Processing [Review Article]. IEEE Comput. Intell. Mag. 13(3): 55-75 (2018)
[j71]
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Frank Z. Xing, Erik Cambria, Roy E. Welsch:
Intelligent Asset Allocation via Market Sentiment Views. IEEE Comput. Intell. Mag. 13(4): 25-34 (2018)
[j70]
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Yukun Ma, Haiyun Peng, Tahir Khan, Erik Cambria, Amir Hussain:
Sentic LSTM: a Hybrid Network for Targeted Aspect-Based Sentiment Analysis. Cogn. Comput. 10(4): 639-650 (2018)
[j69]
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Anupam Mondal, Erik Cambria, Dipankar Das, Amir Hussain, Sivaji Bandyopadhyay:
Relation Extraction of Medical Concepts Using Categorization and Sentiment Analysis. Cogn. Comput. 10(4): 670-685 (2018)
[j68]
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Lorenzo Malandri, Frank Z. Xing, Carlotta Orsenigo, Carlo Vercellis, Erik Cambria:
Public Mood-Driven Asset Allocation: the Importance of Financial Sentiment in Portfolio Management. Cogn. Comput. 10(6): 1167-1176 (2018)
[j67]
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Mauro Dragoni, Soujanya Poria, Erik Cambria:
OntoSenticNet: A Commonsense Ontology for Sentiment Analysis. IEEE Intell. Syst. 33(3): 77-85 (2018)
[j66]
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Soujanya Poria, Navonil Majumder, Devamanyu Hazarika, Erik Cambria, Alexander F. Gelbukh, Amir Hussain:
Multimodal Sentiment Analysis: Addressing Key Issues and Setting Up the Baselines. IEEE Intell. Syst. 33(6): 17-25 (2018)
[j65]
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  - journals/ijon/HussainC18
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Amir Hussain, Erik Cambria:
Semi-supervised learning for big social data analysis. Neurocomputing 275: 1662-1673 (2018)
[j64]
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  - journals/inffus/ChaturvediCWH18
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Iti Chaturvedi, Erik Cambria, Roy E. Welsch, Francisco Herrera:
Distinguishing between facts and opinions for sentiment analysis: Survey and challenges. Inf. Fusion 44: 65-77 (2018)
[j63]
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Ana Valdivia, María Victoria Luzón, Erik Cambria, Francisco Herrera:
Consensus vote models for detecting and filtering neutrality in sentiment analysis. Inf. Fusion 44: 126-135 (2018)
[j62]
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Yang Li, Quan Pan, Suhang Wang, Tao Yang, Erik Cambria:
A Generative Model for category text generation. Inf. Sci. 450: 301-315 (2018)
[j61]
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Iti Chaturvedi, Edoardo Ragusa, Paolo Gastaldo, Rodolfo Zunino, Erik Cambria:
Bayesian network based extreme learning machine for subjectivity detection. J. Frankl. Inst. 355(4): 1780-1797 (2018)
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Haiyun Peng, Yukun Ma, Yang Li, Erik Cambria:
Learning multi-grained aspect target sequence for Chinese sentiment analysis. Knowl. Based Syst. 148: 167-176 (2018)
[j59]
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Navonil Majumder, Devamanyu Hazarika, Alexander F. Gelbukh, Erik Cambria, Soujanya Poria:
Multimodal sentiment analysis using hierarchical fusion with context modeling. Knowl. Based Syst. 161: 124-133 (2018)
[j58]
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  - journals/memetic/TranC18
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Ha Nguyen Tran, Erik Cambria:
Ensemble application of ELM and GPU for real-time multimodal sentiment analysis. Memetic Comput. 10(1): 3-13 (2018)
[j57]
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Ha Nguyen Tran, Erik Cambria:
A survey of graph processing on graphics processing units. J. Supercomput. 74(5): 2086-2115 (2018)
[c112]
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Erik Cambria, Soujanya Poria, Devamanyu Hazarika, Kenneth Kwok:
SenticNet 5: Discovering Conceptual Primitives for Sentiment Analysis by Means of Context Embeddings. AAAI 2018: 1795-1802
[c111]
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Tom Young, Erik Cambria, Iti Chaturvedi, Hao Zhou, Subham Biswas, Minlie Huang:
Augmenting End-to-End Dialogue Systems With Commonsense Knowledge. AAAI 2018: 4970-4977
[c110]
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Amir Zadeh, Paul Pu Liang, Navonil Mazumder, Soujanya Poria, Erik Cambria, Louis-Philippe Morency:
Memory Fusion Network for Multi-view Sequential Learning. AAAI 2018: 5634-5641
[c109]
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Amir Zadeh, Paul Pu Liang, Soujanya Poria, Prateek Vij, Erik Cambria, Louis-Philippe Morency:
Multi-attention Recurrent Network for Human Communication Comprehension. AAAI 2018: 5642-5649
[c108]
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Yukun Ma, Haiyun Peng, Erik Cambria:
Targeted Aspect-Based Sentiment Analysis via Embedding Commonsense Knowledge into an Attentive LSTM. AAAI 2018: 5876-5883
[c107]
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Amir Zadeh, Paul Pu Liang, Soujanya Poria, Erik Cambria, Louis-Philippe Morency:
Multimodal Language Analysis in the Wild: CMU-MOSEI Dataset and Interpretable Dynamic Fusion Graph. ACL (1) 2018: 2236-2246
[c106]
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Aparup Khatua, Erik Cambria, Apalak Khatua:
Sounds of Silence Breakers: Exploring Sexual Violence on Twitter. ASONAM 2018: 397-400
[c105]
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Gangeshwar Krishnamurthy, Navonil Majumder, Soujanya Poria, Erik Cambria:
A Deep Learning Approach for Multimodal Deception Detection. CICLing (1) 2018: 87-96
[c104]
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Rajiv Bajpai, Devamanyu Hazarika, Kunal Singh, Sruthi Gorantla, Erik Cambria, Roger Zimmermann:
Aspect-Sentiment Embeddings for Company Profiling and Employee Opinion Mining. CICLing (2) 2018: 142-160
[c103]
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Qian Chen, Edoardo Ragusa, Iti Chaturvedi, Erik Cambria, Rodolfo Zunino:
Text-Image Sentiment Analysis. CICLing (2) 2018: 169-180
[c102]
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Devamanyu Hazarika, Soujanya Poria, Sruthi Gorantla, Erik Cambria, Roger Zimmermann, Rada Mihalcea:
CASCADE: Contextual Sarcasm Detection in Online Discussion Forums. COLING 2018: 1837-1848
[c101]
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Devamanyu Hazarika, Soujanya Poria, Rada Mihalcea, Erik Cambria, Roger Zimmermann:
ICON: Interactive Conversational Memory Network for Multimodal Emotion Detection. EMNLP 2018: 2594-2604
[c100]
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Navonil Majumder, Soujanya Poria, Alexander F. Gelbukh, Md. Shad Akhtar, Erik Cambria, Asif Ekbal:
IARM: Inter-Aspect Relation Modeling with Memory Networks in Aspect-Based Sentiment Analysis. EMNLP 2018: 3402-3411
[c99]
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Mauro Dragoni, Erik Cambria:
Semantic Sentiment Analysis Challenge at ESWC2018. SemWebEval@ESWC 2018: 117-128
[c98]
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  - conf/icdm/AlhussienCN18
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Ikhlas Alhussien, Erik Cambria, Zhang NengSheng:
Semantically Enhanced Models for Commonsense Knowledge Acquisition. ICDM Workshops 2018: 1014-1021
[c97]
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  - conf/icdm/MerelloRMOC18
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Simone Merello, Andrea Picasso Ratto, Yukun Ma, Luca Oneto, Erik Cambria:
Investigating Timing and Impact of News on the Stock Market. ICDM Workshops 2018: 1348-1354
[c96]
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Devamanyu Hazarika, Soujanya Poria, Prateek Vij, Gangeshwar Krishnamurthy, Erik Cambria, Roger Zimmermann:
Modeling Inter-Aspect Dependencies for Aspect-Based Sentiment Analysis. NAACL-HLT (2) 2018: 266-270
[c95]
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Devamanyu Hazarika, Soujanya Poria, Amir Zadeh, Erik Cambria, Louis-Philippe Morency, Roger Zimmermann:
Conversational Memory Network for Emotion Recognition in Dyadic Dialogue Videos. NAACL-HLT 2018: 2122-2132
[c94]
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  - conf/pkdd/XingCMV18
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Frank Z. Xing, Erik Cambria, Lorenzo Malandri, Carlo Vercellis:
Discovering Bayesian Market Views for Intelligent Asset Allocation. ECML/PKDD (3) 2018: 120-135
[c93]
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  - conf/ssci/QianCPCM18
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Qian Chen, Iti Chaturvedi, Soujanya Poria, Erik Cambria, Lorenzo Malandri:
Learning Visual Concepts in Images Using Temporal Convolutional Networks. SSCI 2018: 1280-1284
[c92]
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  - conf/ssci/HoHPC18
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Danyuan Ho, Diyana Hamzah, Soujanya Poria, Erik Cambria:
Singlish SenticNet: A Concept-Based Sentiment Resource for Singapore English. SSCI 2018: 1285-1291
[c91]
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  - conf/ssci/VilaresPSC18
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David Vilares, Haiyun Peng, Ranjan Satapathy, Erik Cambria:
BabelSenticNet: A Commonsense Reasoning Framework for Multilingual Sentiment Analysis. SSCI 2018: 1292-1298
[c90]
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  - conf/ssci/RattoMOMMC18
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Andrea Picasso Ratto, Simone Merello, Luca Oneto, Yukun Ma, Lorenzo Malandri, Erik Cambria:
Ensemble of Technical Analysis and Machine Learning for Market Trend Prediction. SSCI 2018: 2090-2096
[c89]
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  - conf/wordnet/MondalDCB18
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Anupam Mondal, Dipankar Das, Erik Cambria, Sivaji Bandyopadhyay:
WME 3.0: An Enhanced and Validated Lexicon of Medical Concepts. GWC 2018: 10-16
[c88]
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  - conf/www/ZhongC18
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Xiaoshi Zhong, Erik Cambria:
Time Expression Recognition Using a Constituent-based Tagging Scheme. WWW 2018: 983-992
[e9]
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  - conf/esws/2018emsasw
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Diego Reforgiato Recupero, Mauro Dragoni, Davide Buscaldi, Mehwish Alam, Erik Cambria:
Proceedings of 4th Workshop on Sentic Computing, Sentiment Analysis, Opinion Mining, and Emotion Detection (EMSASW 2018) Co-located with the 15th Extended Semantic Web Conference 2018 (ESWC 2018), Heraklion, Greece, June 4, 2018. CEUR Workshop Proceedings 2111, CEUR-WS.org 2018 [contents]
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Iti Chaturvedi, Soujanya Poria, Erik Cambria:
Sentiment Analysis, Basic Tasks of. Encyclopedia of Social Network Analysis and Mining. 2nd Ed. 2018
[i25]
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  - journals/corr/abs-1802-00923
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Amir Zadeh, Paul Pu Liang, Soujanya Poria, Prateek Vij, Erik Cambria, Louis-Philippe Morency:
Multi-attention Recurrent Network for Human Communication Comprehension. CoRR abs/1802.00923 (2018)
[i24]
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  - journals/corr/abs-1802-00927
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Amir Zadeh, Paul Pu Liang, Navonil Mazumder, Soujanya Poria, Erik Cambria, Louis-Philippe Morency:
Memory Fusion Network for Multi-view Sequential Learning. CoRR abs/1802.00927 (2018)
[i23]
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  - journals/corr/abs-1802-09911
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Frank Z. Xing, Erik Cambria, Lorenzo Malandri, Carlo Vercellis:
Discovering Bayesian Market Views for Intelligent Asset Allocation. CoRR abs/1802.09911 (2018)
[i22]
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  - journals/corr/abs-1803-00344
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Gangeshwar Krishnamurthy, Navonil Majumder, Soujanya Poria, Erik Cambria:
A Deep Learning Approach for Multimodal Deception Detection. CoRR abs/1803.00344 (2018)
[i21]
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Soujanya Poria, Navonil Majumder, Devamanyu Hazarika, Erik Cambria, Amir Hussain, Alexander F. Gelbukh:
Multimodal Sentiment Analysis: Addressing Key Issues and Setting up Baselines. CoRR abs/1803.07427 (2018)
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Devamanyu Hazarika, Soujanya Poria, Sruthi Gorantla, Erik Cambria, Roger Zimmermann, Rada Mihalcea:
CASCADE: Contextual Sarcasm Detection in Online Discussion Forums. CoRR abs/1805.06413 (2018)
[i19]
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Rhea Sukthanker, Soujanya Poria, Erik Cambria, Ramkumar Thirunavukarasu:
Anaphora and Coreference Resolution: A Review. CoRR abs/1805.11824 (2018)
[i18]
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Navonil Majumder, Devamanyu Hazarika, Alexander F. Gelbukh, Erik Cambria, Soujanya Poria:
Multimodal Sentiment Analysis using Hierarchical Fusion with Context Modeling. CoRR abs/1806.06228 (2018)
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Yukun Ma, Erik Cambria:
Concept-Based Embeddings for Natural Language Processing. CoRR abs/1807.05519 (2018)
[i16]
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Ha Nguyen Tran, Erik Cambria:
GPU-based Commonsense Paradigms Reasoning for Real-Time Query Answering and Multimodal Analysis. CoRR abs/1807.08804 (2018)
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Ikhlas Alhussien, Erik Cambria, Zhang NengSheng:
Semantically Enhanced Models for Commonsense Knowledge Acquisition. CoRR abs/1809.04708 (2018)
[i14]
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Soujanya Poria, Devamanyu Hazarika, Navonil Majumder, Gautam Naik, Erik Cambria, Rada Mihalcea:
MELD: A Multimodal Multi-Party Dataset for Emotion Recognition in Conversations. CoRR abs/1810.02508 (2018)
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Xiaoshi Zhong, Erik Cambria, Jagath C. Rajapakse:
Named Entity Analysis and Extraction with Uncommon Words. CoRR abs/1810.06818 (2018)
[i12]
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Navonil Majumder, Soujanya Poria, Devamanyu Hazarika, Rada Mihalcea, Alexander F. Gelbukh, Erik Cambria:
DialogueRNN: An Attentive RNN for Emotion Detection in Conversations. CoRR abs/1811.00405 (2018)
[i11]
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Xiaoshi Zhong, Erik Cambria, Jagath C. Rajapakse:
Discovering Power Laws in Entity Length. CoRR abs/1811.03325 (2018)
2017
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Siaw Ling Lo, Erik Cambria, Raymond Chiong, David Cornforth:
Multilingual sentiment analysis: from formal to informal and scarce resource languages. Artif. Intell. Rev. 48(4): 499-527 (2017)
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Luca Oneto, Federica Bisio, Erik Cambria, Davide Anguita:
Semi-supervised Learning for Affective Common-Sense Reasoning. Cogn. Comput. 9(1): 18-42 (2017)
[j54]
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Luca Oneto, Federica Bisio, Erik Cambria, Davide Anguita:
SLT-Based ELM for Big Social Data Analysis. Cogn. Comput. 9(2): 259-274 (2017)
[j53]
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Haiyun Peng, Erik Cambria, Amir Hussain:
A Review of Sentiment Analysis Research in Chinese Language. Cogn. Comput. 9(4): 423-435 (2017)
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Erik Cambria, Anupam Chattopadhyay, Eike Linn, Bappaditya Mandal, Bebo White:
Storages Are Not Forever. Cogn. Comput. 9(5): 646-658 (2017)
[j51]
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Yang Li, Quan Pan, Tao Yang, Suhang Wang, Jiliang Tang, Erik Cambria:
Learning Word Representations for Sentiment Analysis. Cogn. Comput. 9(6): 843-851 (2017)
[j50]
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Ranjan Satapathy, Iti Chaturvedi, Erik Cambria, Shirley S. Ho, Jin-Cheon Na:
Subjectivity Detection in Nuclear Energy Tweets. Computación y Sistemas 21(4) (2017)
[j49]
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Navonil Majumder, Soujanya Poria, Alexander F. Gelbukh, Erik Cambria:
Deep Learning-Based Document Modeling for Personality Detection from Text. IEEE Intell. Syst. 32(2): 74-79 (2017)
[j48]
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Erik Cambria, Soujanya Poria, Alexander F. Gelbukh, Mike Thelwall:
Sentiment Analysis Is a Big Suitcase. IEEE Intell. Syst. 32(6): 74-80 (2017)
[j47]
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Soujanya Poria, Haiyun Peng, Amir Hussain, Newton Howard, Erik Cambria:
Ensemble application of convolutional neural networks and multiple kernel learning for multimodal sentiment analysis. Neurocomputing 261: 217-230 (2017)
[j46]
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Soujanya Poria, Erik Cambria, Rajiv Bajpai, Amir Hussain:
A review of affective computing: From unimodal analysis to multimodal fusion. Inf. Fusion 37: 98-125 (2017)
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Erik Cambria, Amir Hussain, Alessandro Vinciarelli:
Affective Reasoning for Big Social Data Analysis. IEEE Trans. Affect. Comput. 8(4): 426-427 (2017)
[c87]
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Xiaoshi Zhong, Aixin Sun, Erik Cambria:
Time Expression Analysis and Recognition Using Syntactic Token Types and General Heuristic Rules. ACL (1) 2017: 420-429
[c86]
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Soujanya Poria, Erik Cambria, Devamanyu Hazarika, Navonil Majumder, Amir Zadeh, Louis-Philippe Morency:
Context-Dependent Sentiment Analysis in User-Generated Videos. ACL (1) 2017: 873-883
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Haiyun Peng, Erik Cambria:
CSenticNet: A Concept-Level Resource for Sentiment Analysis in Chinese Language. CICLing (2) 2017: 90-104
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Erik Cambria, Devamanyu Hazarika, Soujanya Poria, Amir Hussain, R. B. V. Subramanyam:
Benchmarking Multimodal Sentiment Analysis. CICLing (2) 2017: 166-179
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Yukun Ma, Erik Cambria, Benjamin Bigot:
ASR Hypothesis Reranking Using Prior-Informed Restricted Boltzmann Machine. CICLing (1) 2017: 503-514
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Ha Nguyen Tran, Erik Cambria, Hoang Giang Do:
Efficient Semantic Search Over Structured Web Data: A GPU Approach. CICLing (2) 2017: 549-562
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Frank Z. Xing, Danyuan Ho, Diyana Hamzah, Erik Cambria:
Classifying World Englishes from a Lexical Perspective: A Corpus-Based Approach. CICLing (1) 2017: 564-575
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Sandro Cavallari, Vincent W. Zheng, Hongyun Cai, Kevin Chen-Chuan Chang, Erik Cambria:
Learning Community Embedding with Community Detection and Node Embedding on Graphs. CIKM 2017: 377-386
[c79]
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Aishwarya N. Reganti, Tushar Maheshwari, Amitava Das, Erik Cambria:
Open Secrets and Wrong Rights: Automatic Satire Detection in English Text. CSCW Companion 2017: 291-294
[c78]
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Amir Zadeh, Minghai Chen, Soujanya Poria, Erik Cambria, Louis-Philippe Morency:
Tensor Fusion Network for Multimodal Sentiment Analysis. EMNLP 2017: 1103-1114
[c77]
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Diego Reforgiato Recupero, Erik Cambria, Emanuele Di Rosa:
Semantic Sentiment Analysis Challenge at ESWC2017. SemWebEval@ESWC 2017: 109-123
[c76]
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Iti Chaturvedi, Erik Cambria, Sandro Cavallari, Vincent Wenchen Zheng:
Learning Word Vectors in Deep Walk using Convolution. FLAIRS 2017: 323-328
[c75]
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Anupam Mondal, Erik Cambria, Dipankar Das, Sivaji Bandyopadhyay:
MediConceptNet: An Affinity Score Based Medical Concept Network. FLAIRS 2017: 335-340
[c74]
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Haiyun Peng, Erik Cambria, Xiaomei Zou:
Radical-Based Hierarchical Embeddings for Chinese Sentiment Analysis at Sentence Level. FLAIRS 2017: 347-352
[c73]
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Ceyda Sanli, Anupam Mondal, Erik Cambria:
Tracing Linguistic Relations in Winning and Losing Sides of Explicit Opposing Groups. FLAIRS 2017: 365-370
[c72]
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Mimansa Jaiswal, Sairam Tabibu, Erik Cambria:
"Hang In There: " Lexical and Visual Analysis to Identify Posts Warranting Empathetic Responses. FLAIRS 2017: 377-381
[c71]
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Aparup Khatua, Erik Cambria, Apalak Khatua, Iti Chaturvedi:
Let's Chat about Brexit! A Politically-Sensitive Dialog System Based on Twitter Data. ICDM Workshops 2017: 393-398
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Ranjan Satapathy, Claudia Guerreiro, Iti Chaturvedi, Erik Cambria:
Phonetic-Based Microtext Normalization for Twitter Sentiment Analysis. ICDM Workshops 2017: 407-413
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Soujanya Poria, Erik Cambria, Devamanyu Hazarika, Navonil Majumder, Amir Zadeh, Louis-Philippe Morency:
Multi-level Multiple Attentions for Contextual Multimodal Sentiment Analysis. ICDM 2017: 1033-1038
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Guibin Chen, Deheng Ye, Zhenchang Xing, Jieshan Chen, Erik Cambria:
Ensemble application of convolutional and recurrent neural networks for multi-label text categorization. IJCNN 2017: 2377-2383
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Frank Z. Xing, Erik Cambria, Xiaomei Zou:
Predicting evolving chaotic time series with fuzzy neural networks. IJCNN 2017: 3176-3183
[c66]
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Chi Xu, Puay Siew Tan, Erik Cambria:
Adaptive two-stage feature selection for sentiment classification. SMC 2017: 1238-1243
[c65]
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Anupam Mondal, Erik Cambria, Dipankar Das, Sivaji Bandyopadhyay:
Employing sentiment-based affinity and gravity scores to identify relations of medical concepts. SSCI 2017: 1-7
[c64]
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Anupam Mondal, Erik Cambria, Antonio Feraco, Dipankar Das, Sivaji Bandyopadhyay:
Auto-categorization of medical concepts and contexts. SSCI 2017: 1-7
[i10]
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Ceyda Sanli, Anupam Mondal, Erik Cambria:
Tracing Linguistic Relations in Winning and Losing Sides of Explicit Opposing Groups. CoRR abs/1703.00317 (2017)
[i9]
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Rajiv Bajpai, Soujanya Poria, Danyuan Ho, Erik Cambria:
Developing a concept-level knowledge base for sentiment analysis in Singlish. CoRR abs/1707.04408 (2017)
[i8]
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Amir Zadeh, Minghai Chen, Soujanya Poria, Erik Cambria, Louis-Philippe Morency:
Tensor Fusion Network for Multimodal Sentiment Analysis. CoRR abs/1707.07250 (2017)
[i7]
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Erik Cambria, Devamanyu Hazarika, Soujanya Poria, Amir Hussain, R. B. V. Subramanyam:
Benchmarking Multimodal Sentiment Analysis. CoRR abs/1707.09538 (2017)
[i6]
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Tom Young, Devamanyu Hazarika, Soujanya Poria, Erik Cambria:
Recent Trends in Deep Learning Based Natural Language Processing. CoRR abs/1708.02709 (2017)
[i5]
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Yang Li, Quan Pan, Suhang Wang, Haiyun Peng, Tao Yang, Erik Cambria:
Disentangled Variational Auto-Encoder for Semi-supervised Learning. CoRR abs/1709.05047 (2017)
[i4]
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Iti Chaturvedi, Soujanya Poria, Erik Cambria:
Basic tasks of sentiment analysis. CoRR abs/1710.06536 (2017)
2016
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Atika Qazi, Karim Bux Shah Syed, Ram Gopal Raj, Erik Cambria, Muhammad Tahir, Daniyal M. Al-Ghazzawi:
A concept-level approach to the analysis of online review helpfulness. Comput. Hum. Behav. 58: 75-81 (2016)
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Erik Cambria, Newton Howard, Yunqing Xia, Tat-Seng Chua:
Computational Intelligence for Big Social Data Analysis [Guest Editorial]. IEEE Comput. Intell. Mag. 11(3): 8-9 (2016)
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Luca Oneto, Federica Bisio, Erik Cambria, Davide Anguita:
Statistical Learning Theory and ELM for Big Social Data Analysis. IEEE Comput. Intell. Mag. 11(3): 45-55 (2016)
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Nir Ofek, Soujanya Poria, Lior Rokach, Erik Cambria, Amir Hussain, Asaf Shabtai:
Unsupervised Commonsense Knowledge Enrichment for Domain-Specific Sentiment Analysis. Cogn. Comput. 8(3): 467-477 (2016)
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Kia Dashtipour, Soujanya Poria, Amir Hussain, Erik Cambria, Ahmad Y. A. Hawalah, Alexander F. Gelbukh, Qiang Zhou:
Multilingual Sentiment Analysis: State of the Art and Independent Comparison of Techniques. Cogn. Comput. 8(4): 757-771 (2016)
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Kia Dashtipour, Soujanya Poria, Amir Hussain, Erik Cambria, Ahmad Y. A. Hawalah, Alexander F. Gelbukh, Qiang Zhou:
Erratum to: Multilingual Sentiment Analysis: State of the Art and Independent Comparison of Techniques. Cogn. Comput. 8(4): 772-775 (2016)
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Ha Nguyen Tran, Erik Cambria, Amir Hussain:
Towards GPU-Based Common-Sense Reasoning: Using Fast Subgraph Matching. Cogn. Comput. 8(6): 1074-1086 (2016)
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Erik Cambria:
Affective Computing and Sentiment Analysis. IEEE Intell. Syst. 31(2): 102-107 (2016)
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Soujanya Poria, Erik Cambria, Newton Howard, Guang-Bin Huang, Amir Hussain:
Fusing audio, visual and textual clues for sentiment analysis from multimodal content. Neurocomputing 174: 50-59 (2016)
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Paolo Rosso, Cristina Bosco, Rossana Damiano, Viviana Patti, Erik Cambria:
Emotion and sentiment in social and expressive media: Introduction to the special issue. Inf. Process. Manag. 52(1): 1-4 (2016)
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Rui Xia, Feng Xu, Jianfei Yu, Yong Qi, Erik Cambria:
Polarity shift detection, elimination and ensemble: A three-stage model for document-level sentiment analysis. Inf. Process. Manag. 52(1): 36-45 (2016)
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Siaw Ling Lo, Erik Cambria, Raymond Chiong, David Cornforth:
A multilingual semi-supervised approach in deriving Singlish sentic patterns for polarity detection. Knowl. Based Syst. 105: 236-247 (2016)
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Erik Cambria, Björn W. Schuller, Yunqing Xia, Bebo White:
New avenues in knowledge bases for natural language processing. Knowl. Based Syst. 108: 1-4 (2016)
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Soujanya Poria, Erik Cambria, Alexander F. Gelbukh:
Aspect extraction for opinion mining with a deep convolutional neural network. Knowl. Based Syst. 108: 42-49 (2016)
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Iti Chaturvedi, Yew-Soon Ong, Ivor W. Tsang, Roy E. Welsch, Erik Cambria:
Learning word dependencies in text by means of a deep recurrent belief network. Knowl. Based Syst. 108: 144-154 (2016)
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Kia Dashtipour, Amir Hussain, Qiang Zhou, Alexander F. Gelbukh, Ahmad Y. A. Hawalah, Erik Cambria:
PerSent: A Freely Available Persian Sentiment Lexicon. BICS 2016: 310-320
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Rajiv Bajpai, Danyuan Ho, Erik Cambria:
Developing a Concept-Level Knowledge Base for Sentiment Analysis in Singlish. CICLing (2) 2016: 347-361
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Ha Nguyen Tran, Erik Cambria:
GpSense: A GPU-Friendly Method for Commonsense Subgraph Matching in Massively Parallel Architectures. CICLing (1) 2016: 547-559
[c60]
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Yukun Ma, Erik Cambria, Sa Gao:
Label Embedding for Zero-shot Fine-grained Named Entity Typing. COLING 2016: 171-180
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Soujanya Poria, Erik Cambria, Devamanyu Hazarika, Prateek Vij:
A Deeper Look into Sarcastic Tweets Using Deep Convolutional Neural Networks. COLING 2016: 1601-1612
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Erik Cambria, Soujanya Poria, Rajiv Bajpai, Björn W. Schuller:
SenticNet 4: A Semantic Resource for Sentiment Analysis Based on Conceptual Primitives. COLING 2016: 2666-2677
[c57]
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Erik Cambria, Tam V. Nguyen, Brian Cheng, Kenneth Kwok, Jose Sepulveda:
GECKA3D: A 3D Game Engine for Commonsense Knowledge Acquisition. FLAIRS 2016: 299-303
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Soujanya Poria, Iti Chaturvedi, Erik Cambria, Amir Hussain:
Convolutional MKL Based Multimodal Emotion Recognition and Sentiment Analysis. ICDM 2016: 439-448
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Iti Chaturvedi, Erik Cambria, Soujanya Poria, Rajiv Bajpai:
Bayesian Deep Convolution Belief Networks for Subjectivity Detection. ICDM Workshops 2016: 916-923
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Frank Z. Xing, Erik Cambria, Win-Bin Huang, Yang Xu:
Weakly supervised semantic segmentation with superpixel embedding. ICIP 2016: 1269-1273
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Soujanya Poria, Iti Chaturvedi, Erik Cambria, Federica Bisio:
Sentic LDA: Improving on LDA with semantic similarity for aspect-based sentiment analysis. IJCNN 2016: 4465-4473
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Iti Chaturvedi, Erik Cambria, David Vilares:
Lyapunov filtering of objectivity for Spanish Sentiment Model. IJCNN 2016: 4474-4481
[c51]
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Anupam Mondal, Dipankar Das, Erik Cambria, Sivaji Bandyopadhyay:
WME: Sense, Polarity and Affinity based Concept Resource for Medical Events. GWC 2016: 243-248
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Federica Bisio, Claudia Meda, Paolo Gastaldo, Rodolfo Zunino, Erik Cambria:
Sentiment-Oriented Information Retrieval: Affective Analysis of Documents Based on the SenticNet Framework. Sentiment Analysis and Ontology Engineering 2016: 175-197
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Sivaji Bandyopadhyay, Dipankar Das, Erik Cambria, Braja Gopal Patra:
Proceedings of the 4th Workshop on Sentiment Analysis where AI meets Psychology (SAAIP 2016) co-located with 25th International Joint Conference on Artificial Intelligence (IJCAI 2016), New York City, USA, July 10, 2016. CEUR Workshop Proceedings 1619, CEUR-WS.org 2016 [contents]
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Erik Cambria, Tam V. Nguyen, Brian Cheng, Kenneth Kwok, Jose Sepulveda:
GECKA3D: A 3D Game Engine for Commonsense Knowledge Acquisition. CoRR abs/1602.01178 (2016)
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Soujanya Poria, Erik Cambria, Devamanyu Hazarika, Prateek Vij:
A Deeper Look into Sarcastic Tweets Using Deep Convolutional Neural Networks. CoRR abs/1610.08815 (2016)
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Vincent W. Zheng, Sandro Cavallari, Hongyun Cai, Kevin Chen-Chuan Chang, Erik Cambria:
From Node Embedding To Community Embedding. CoRR abs/1610.09950 (2016)
2015
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Guang-Bin Huang, Erik Cambria, Kar-Ann Toh, Bernard Widrow, Zongben Xu:
New Trends of Learning in Computational Intelligence [Guest Editorial]. IEEE Comput. Intell. Mag. 10(2): 16-17 (2015)
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Guang-Bin Huang, Erik Cambria, Kar-Ann Toh, Bernard Widrow, Zongben Xu:
New Trends of Learning in Computational Intelligence (Part II) [Guest Editorial]. IEEE Comput. Intell. Mag. 10(3): 8 (2015)
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Soujanya Poria, Erik Cambria, Alexander F. Gelbukh, Federica Bisio, Amir Hussain:
Sentiment Data Flow Analysis by Means of Dynamic Linguistic Patterns. IEEE Comput. Intell. Mag. 10(4): 26-36 (2015)
[j26]
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Erik Cambria, Amir Hussain:
Sentic Computing. Cogn. Comput. 7(2): 183-185 (2015)
[j25]
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Yunqing Xia, Erik Cambria, Amir Hussain:
AspNet: Aspect Extraction by Bootstrapping Generalization and Propagation Using an Aspect Network. Cogn. Comput. 7(2): 241-253 (2015)
[j24]
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Yunqing Xia, Erik Cambria, Amir Hussain, Huan Zhao:
Word Polarity Disambiguation Using Bayesian Model and Opinion-Level Features. Cogn. Comput. 7(3): 369-380 (2015)
[j23]
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Emanuele Principi, Stefano Squartini, Erik Cambria, Francesco Piazza:
Acoustic template-matching for automatic emergency state detection: An ELM based algorithm. Neurocomputing 149: 426-434 (2015)
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Erik Cambria, Paolo Gastaldo, Federica Bisio, Rodolfo Zunino:
An ELM-based model for affective analogical reasoning. Neurocomputing 149: 443-455 (2015)
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Guoyu Tang, Yunqing Xia, Erik Cambria, Peng Jin, Thomas Fang Zheng:
Document Representation with Statistical Word Senses in Cross-Lingual Document Clustering. Int. J. Pattern Recognit. Artif. Intell. 29(2): 1559003:1-1559003:26 (2015)
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Soujanya Poria, Erik Cambria, Amir Hussain, Guang-Bin Huang:
Towards an intelligent framework for multimodal affective data analysis. Neural Networks 63: 104-116 (2015)
[c50]
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Erik Cambria, Jie Fu, Federica Bisio, Soujanya Poria:
AffectiveSpace 2: Enabling Affective Intuition for Concept-Level Sentiment Analysis. AAAI 2015: 508-514
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Erik Cambria, Soujanya Poria, Federica Bisio, Rajiv Bajpai, Iti Chaturvedi:
The CLSA Model: A Novel Framework for Concept-Level Sentiment Analysis. CICLing (2) 2015: 3-22
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Prerna Chikersal, Soujanya Poria, Erik Cambria, Alexander F. Gelbukh, Chng Eng Siong:
Modelling Public Sentiment in Twitter: Using Linguistic Patterns to Enhance Supervised Learning. CICLing (2) 2015: 49-65
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Chris Wilson Antuvan, Federica Bisio, Erik Cambria, Lorenzo Masia:
Muscle synergies for reliable classification of arm motions using myoelectric interface. EMBC 2015: 1136-1139
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Soujanya Poria, Erik Cambria, Alexander F. Gelbukh:
Deep Convolutional Neural Network Textual Features and Multiple Kernel Learning for Utterance-level Multimodal Sentiment Analysis. EMNLP 2015: 2539-2544
[c45]
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Erik Cambria, Giuseppe Melfi:
Semantic Outlier Detection for Affective Common-Sense Reasoning and Concept-Level Sentiment Analysis. FLAIRS 2015: 276-281
[c44]
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Erik Cambria, Dheeraj Rajagopal, Kenneth Kwok, Jose Sepulveda:
GECKA: Game Engine for Commonsense Knowledge Acquisition. FLAIRS 2015: 282-287
[c43]
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Yunqing Xia, Nan Tang, Amir Hussain, Erik Cambria:
Discriminative Bi-Term Topic Model for Headline-Based Social News Clustering. FLAIRS 2015: 311-316
[c42]
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Rui Xia, Chengqing Zong, Xuelei Hu, Erik Cambria:
Feature Ensemble Plus Sample Selection: Domain Adaptation for Sentiment Classification (Extended Abstract). IJCAI 2015: 4229-4233
[c41]
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Federica Bisio, Paolo Gastaldo, Rodolfo Zunino, Erik Cambria:
A learning scheme based on similarity functions for affective common-sense reasoning. IJCNN 2015: 1-6
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  - conf/semeval/ChikersalPC15
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Prerna Chikersal, Soujanya Poria, Erik Cambria:
SeNTU: Sentiment Analysis of Tweets by Combining a Rule-based Classifier with Supervised Learning. SemEval@NAACL-HLT 2015: 647-651
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Shou-de Lin, Lun-Wei Ku, Cheng-Te Li, Erik Cambria:
Proceedings of the third International Workshop on Natural Language Processing for Social Media, SocialNLP@NAACL 2015, Denver, Colorado, USA, June 5, 2015. Association for Computational Linguistics 2015, ISBN 978-1-941643-48-8 [contents]
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Cristina Bosco, Erik Cambria, Rossana Damiano, Viviana Patti, Paolo Rosso:
Proceedings of the 2nd International Workshop on Emotion and Sentiment in Social and Expressive Media: Opportunities and Challenges for Emotion-aware Multiagent Systems co-located with 14th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2015), Istanbul, Turkey, May 5, 2015. CEUR Workshop Proceedings 1351, CEUR-WS.org 2015 [contents]
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Aldo Gangemi, Harith Alani, Malvina Nissim, Erik Cambria, Diego Reforgiato Recupero, Vitaveska Lanfranchi, Tomi Kauppinen:
Joint Proceedings of the 1th Workshop on Semantic Sentiment Analysis (SSA2014), and the Workshop on Social Media and Linked Data for Emergency Response (SMILE 2014) co-located with 11th European Semantic Web Conference (ESWC 2014), Crete, Greece, May 25th, 2014. CEUR Workshop Proceedings 1329, CEUR-WS.org 2015 [contents]
2014
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Erik Cambria, Bebo White, Tariq S. Durrani, Newton Howard:
Computational Intelligence for Natural Language Processing [Guest Editorial]. IEEE Comput. Intell. Mag. 9(1): 19-63 (2014)
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Erik Cambria, Bebo White:
Jumping NLP Curves: A Review of Natural Language Processing Research [Review Article]. IEEE Comput. Intell. Mag. 9(2): 48-57 (2014)
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Erik Cambria, Yangqiu Song, Haixun Wang, Newton Howard:
Semantic Multidimensional Scaling for Open-Domain Sentiment Analysis. IEEE Intell. Syst. 29(2): 44-51 (2014)
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Erik Cambria, Haixun Wang, Bebo White:
Guest Editorial: Big Social Data Analysis. Knowl. Based Syst. 69: 1-2 (2014)
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Soujanya Poria, Erik Cambria, Grégoire Winterstein, Guang-Bin Huang:
Sentic patterns: Dependency-based rules for concept-level sentiment analysis. Knowl. Based Syst. 69: 45-63 (2014)
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Soujanya Poria, Alexander F. Gelbukh, Erik Cambria, Amir Hussain, Guang-Bin Huang:
EmoSenticSpace: A novel framework for affective common-sense reasoning. Knowl. Based Syst. 69: 108-123 (2014)
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Amir Hussain, Erik Cambria, Björn W. Schuller, Newton Howard:
Affective neural networks and cognitive learning systems for big data analysis. Neural Networks 58: 1-3 (2014)
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Erik Cambria, Daniel Olsher, Dheeraj Rajagopal:
SenticNet 3: A Common and Common-Sense Knowledge Base for Cognition-Driven Sentiment Analysis. AAAI 2014: 1515-1521
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Soujanya Poria, Erik Cambria, Lun-Wei Ku, Chen Gui, Alexander F. Gelbukh:
A Rule-Based Approach to Aspect Extraction from Product Reviews. SocialNLP@COLING 2014: 28-37
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Diego Reforgiato Recupero, Erik Cambria:
ESWC'14 Challenge on Concept-Level Sentiment Analysis. SemWebEval@ESWC 2014: 3-20
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Erik Cambria, Newton Howard:
Common and Common-Sense Knowledge Integration for Concept-Level Sentiment Analysis. FLAIRS 2014
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Yunqing Xia, Guoyu Tang, Huan Zhao, Erik Cambria, Thomas Fang Zheng:
Using Word Sense as a Latent Variable in LDA Can Improve Topic Modeling. ICAART (1) 2014: 532-537
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Andrés Gómez de Silva Garza, Erik Cambria, Rafael Pérez y Pérez:
Commonsense Knowledge as the Glue in a Hybrid Model of Computational Creativity. ICDM Workshops 2014: 360-364
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Yunqing Xia, Xiaoyu Li, Erik Cambria, Amir Hussain:
A Localization Toolkit for Sentic Net. ICDM Workshops 2014: 403-408
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Erik Cambria, Soujanya Poria, Alexander F. Gelbukh, Kenneth Kwok:
Sentic API: A Common and Common-Sense Knowledge API for Cognition-Driven Sentiment Analysis. #MSM 2014: 19-24
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Erik Cambria:
Concept-level sentiment analysis: a world wide web conference 2014 tutorial. WWW (Companion Volume) 2014: 187-188
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Emanuele Lunadei, Christian Valdivia Torres, Erik Cambria:
Collective copyright: enabling the natural evolution of content creation in the web era. WWW (Companion Volume) 2014: 1103-1108
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Shou-de Lin, Lun-Wei Ku, Erik Cambria, Tsung-Ting Kuo:
Proceedings of the Second Workshop on Natural Language Processing for Social Media, SocialNLP@COLING 2014, Dublin, Ireland, August 24, 2014. Association for Computational Linguistics and Dublin City University 2014, ISBN 978-1-873769-45-4 [contents]
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Valentina Presutti, Milan Stankovic, Erik Cambria, Iván Cantador, Angelo Di Iorio, Tommaso Di Noia, Christoph Lange, Diego Reforgiato Recupero, Anna Tordai:
Semantic Web Evaluation Challenge - SemWebEval 2014 at ESWC 2014, Anissaras, Crete, Greece, May 25-29, 2014, Revised Selected Papers. Communications in Computer and Information Science 475, Springer 2014, ISBN 978-3-319-12023-2 [contents]
2013
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Qiu-Feng Wang, Erik Cambria, Cheng-Lin Liu, Amir Hussain:
Common Sense Knowledge for Handwritten Chinese Text Recognition. Cogn. Comput. 5(2): 234-242 (2013)
[j11]
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Erik Cambria, Björn W. Schuller, Bing Liu, Haixun Wang, Catherine Havasi:
Knowledge-Based Approaches to Concept-Level Sentiment Analysis. IEEE Intell. Syst. 28(2): 12-14 (2013)
[j10]
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Erik Cambria, Björn W. Schuller, Yunqing Xia, Catherine Havasi:
New Avenues in Opinion Mining and Sentiment Analysis. IEEE Intell. Syst. 28(2): 15-21 (2013)
[j9]
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Erik Cambria, Björn W. Schuller, Bing Liu, Haixun Wang, Catherine Havasi:
Statistical Approaches to Concept-Level Sentiment Analysis. IEEE Intell. Syst. 28(3): 6-9 (2013)
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Rui Xia, Chengqing Zong, Xuelei Hu, Erik Cambria:
Feature Ensemble Plus Sample Selection: Domain Adaptation for Sentiment Classification. IEEE Intell. Syst. 28(3): 10-18 (2013)
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Erik Cambria, Guang-Bin Huang, Liyanaarachchi Lekamalage Chamara Kasun, Hongming Zhou, Chi-Man Vong, Jiarun Lin, Jianping Yin, Zhiping Cai, Qiang Liu, Kuan Li, Victor C. M. Leung, Liang Feng, Yew-Soon Ong, Meng-Hiot Lim, Anton Akusok, Amaury Lendasse, Francesco Corona, Rui Nian, Yoan Miche, Paolo Gastaldo, Rodolfo Zunino, Sergio Decherchi, Xuefeng Yang, Kezhi Mao, Beom-Seok Oh, Je-Hyoung Jeon, Kar-Ann Toh, Andrew Beng Jin Teoh, Jaihie Kim, Hanchao Yu, Yiqiang Chen, Junfa Liu:
Extreme Learning Machines. IEEE Intell. Syst. 28(6): 30-59 (2013)
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Newton Howard, Erik Cambria:
Intention awareness: improving upon situation awareness in human-centric environments. Hum. centric Comput. Inf. Sci. 3: 9 (2013)
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Sergio Decherchi, Paolo Gastaldo, Rodolfo Zunino, Erik Cambria, Judith Redi:
Circular-ELM for the reduced-reference assessment of perceived image quality. Neurocomputing 102: 78-89 (2013)
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Federica Bisio, Paolo Gastaldo, Chiara Peretti, Rodolfo Zunino, Erik Cambria:
Data intensive review mining for sentiment classification across heterogeneous domains. ASONAM 2013: 1061-1067
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Erik Cambria, Newton Howard, Jane Yung-jen Hsu, Amir Hussain:
Sentic blending: Scalable multimodal fusion for the continuous interpretation of semantics and sentics. CIHLI 2013: 108-117
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Guoyu Tang, Yunqing Xia, Erik Cambria, Peng Jin:
Inducing Word Senses for Cross-lingual Document Clustering. CIS 2013: 409-414
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Basant Agarwal, Namita Mittal, Erik Cambria:
Enhancing Sentiment Classification Performance Using Bi-Tagged Phrases. ICDM Workshops 2013: 892-895
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Dheeraj Rajagopal, Daniel Olsher, Erik Cambria, Kenneth Kwok:
Commonsense-based topic modeling. WISDOM 2013: 6:1-6:8
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Erik Cambria:
An Introduction to Concept-Level Sentiment Analysis. MICAI (2) 2013: 478-483
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Soujanya Poria, Alexander F. Gelbukh, Basant Agarwal, Erik Cambria, Newton Howard:
Common Sense Knowledge Based Personality Recognition from Text. MICAI (2) 2013: 484-496
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Soujanya Poria, Alexander F. Gelbukh, Basant Agarwal, Erik Cambria, Newton Howard:
Erratum: Common Sense Knowledge Based Personality Recognition from Text. MICAI (2) 2013
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Dheeraj Rajagopal, Erik Cambria, Daniel Olsher, Kenneth Kwok:
A graph-based approach to commonsense concept extraction and semantic similarity detection. WWW (Companion Volume) 2013: 565-570
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Erik Cambria, Marco Grassi, Soujanya Poria, Amir Hussain:
Sentic Computing for Social Media Analysis, Representation, and Retrieval. Social Media Retrieval 2013: 191-215
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Cristina Battaglino, Cristina Bosco, Erik Cambria, Rossana Damiano, Viviana Patti, Paolo Rosso:
Proceedings of the First International Workshop on Emotion and Sentiment in Social and Expressive Media: approaches and perspectives from AI (ESSEM 2013) A workshop of the XIII International Conference of the Italian Association for Artificial Intelligence (AI*IA 2013), Turin, Italy, December 3, 2013. CEUR Workshop Proceedings 1096, CEUR-WS.org 2013 [contents]
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Erik Cambria, Bing Liu, Yongzheng Zhang, Yunqing Xia:
Proceedings of the Second International Workshop on Issues of Sentiment Discovery and Opinion Mining, WISDOM 2013, Chicago, IL, USA, August 11, 2013. ACM 2013, ISBN 978-1-4503-2332-1 [contents]
2012
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Erik Cambria, Amir Hussain:
Sentic Album: Content-, Concept-, and Context-Based Online Personal Photo Management System. Cogn. Comput. 4(4): 477-496 (2012)
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Erik Cambria, Tim Benson, Chris Eckl, Amir Hussain:
Sentic PROMs: Application of sentic computing to the development of a novel unified framework for measuring health-care quality. Expert Syst. Appl. 39(12): 10533-10543 (2012)
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Erik Cambria, Marco Grassi, Amir Hussain, Catherine Havasi:
Sentic Computing for social media marketing. Multim. Tools Appl. 59(2): 557-577 (2012)
[c20]
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