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ORCIDCan Wang 0004
Person information
- affiliation: Griffith University, Australia
- affiliation: Commonwealth Scientific and Industrial Research Organisation (CSIRO), Sandy Bay, TAS, Australia
- affiliation (PhD 2013): University of Technology, Sydney, Advanced Analytics Institute, NSW, Australia
Other persons with the same name
- Can Wang — disambiguation page
- Can Wang 0001
![[0000-0002-5890-4307]](https://dblp.uni-trier.de/img/orcid-mark.12x12.png "0000-0002-5890-4307")
— Zhejiang University, College of Computer Science, Zhejiang Provincial Key Laboratory of Service Robot, Hangzhou, China - Can Wang 0002 — Chinese Academy of Sciences, Shenzhen Institutes of Advanced Technology, Guangdong Provincial Key Laboratory of Robotics and Intelligent System, China (and 2 more)
- Can Wang 0003 — Harbin Institute of Technology, State Key Laboratory of Robotics and System, China
- Can Wang 0006 — Peking University, Shenzhen Graduate School, Key Laboratory of Machine Perception, Beijing, China
- Can Wang 0007 — City University of Hong Kong, Department of Computer Science, Chow Yei Ching School of Graduate Studies, Hong Kong (and 1 more)
- Can Wang 0008 — China Three Gorges University, College of Electrical Engineering and New Energy, Yichang, China (and 1 more)
- Can Wang 0009 — Stanford University, CA, USA (and 2 more)
- Can Wang 0010 — Shenzhen University, College of Mechatronics and Control Engineering, China (and 1 more)
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2020 – today
- 2024
[j31]Tianxing Wang, Can Wang:
Embracing LLMs for Point-of-Interest Recommendations. IEEE Intell. Syst. 39(1): 56-59 (2024)- [j30]Chang Guo, Weimin Li, Jingchao Wang, Xiao Yu, Xiao Liu, Alex Munyole Luvembe, Can Wang, Qun Jin:
Heterogeneous network influence maximization algorithm based on multi-scale propagation strength and repulsive force of propagation field. Knowl. Based Syst. 291: 111580 (2024) - 2023
- [j29]Jingchao Wang, Weimin Li, Wei Liu, Can Wang, Qun Jin:
Enabling inductive knowledge graph completion via structure-aware attention network. Appl. Intell. 53(21): 25003-25027 (2023) - [j28]Mengying Wang, Weimin Li, Xiao Yu, Yin Luo, Ke Han, Can Wang, Qun Jin:
AffinityVAE: A multi-objective model for protein-ligand affinity prediction and drug design. Comput. Biol. Chem. 107: 107971 (2023) - [j27]Ye Tao, Can Wang, Alan Wee-Chung Liew:
Dynamic weighted ensemble learning for sequential recommendation systems: The AIRE model. Future Gener. Comput. Syst. 149: 162-170 (2023) - [j26]Weimin Li, Chang Guo, Zhibin Deng, Fangfang Liu, Jianjia Wang, Ruiqiang Guo, Can Wang, Qun Jin:
Coevolution modeling of group behavior and opinion based on public opinion perception. Knowl. Based Syst. 270: 110547 (2023) - [j25]Can Wang, Chi-Hung Chi, Lina Yao, Alan Wee-Chung Liew, Hong Shen:
Interdependence analysis on heterogeneous data via behavior interior dimensions. Knowl. Based Syst. 279: 110893 (2023) - [j24]Ye Tao, Can Wang, Lina Yao, Weimin Li, Yonghong Yu:
Item trend learning for sequential recommendation system using gated graph neural network. Neural Comput. Appl. 35(18): 13077-13092 (2023) - [j23]Weibin Zhao, Lin Shang, Yonghong Yu, Li Zhang, Can Wang, Jiajun Chen:
Personalized tag recommendation via denoising auto-encoder. World Wide Web (WWW) 26(1): 95-114 (2023) - [c41]Bo Li, Jiaxin Ju, Can Wang, Shirui Pan:
How Does ChatGPT Affect Fake News Detection Systems? ADMA (2) 2023: 565-580 - [c40]Tianxing Wang, Can Wang, Hui Tian, Hong Shen:
GeoMixer: The MLP-Based Sequential POI Recommender with Travel Routing Modelling. ICDM 2023: 1373-1378 - [c39]Haonan Ma, Can Wang, Yunwei Zhao, Luhua Wang, Xiulian Cao, Jinyin Chen, Han Han, Meichen Liu:
An in-depth analysis of robustness and accuracy of recommendation systems. ICDM (Workshops) 2023: 1509-1515 - [c38]Tianxing Wang, Can Wang:
Global-Aware External Attention Deep Model for Sequential Recommendation. PAKDD (3) 2023: 335-347 - 2022
- [j22]Ran Liu, Xiang Wang, Can Wang:
An efficient two-factor authentication scheme based on negative databases: Experiments and extensions. Appl. Soft Comput. 119: 108558 (2022) - [j21]Ye Tao, Can Wang, Alan Wee-Chung Liew, Sebastian Binnewies:
Enhancing recommender ensemble by estimating input fitness. Comput. Electr. Eng. 104(Part): 108442 (2022) - [j20]Weimin Li, Yaqiong Li, Wei Liu, Can Wang:
An influence maximization method based on crowd emotion under an emotion-based attribute social network. Inf. Process. Manag. 59(2): 102818 (2022) - [j19]Weimin Li, Lin Ni, Jianjia Wang, Can Wang:
Collaborative representation learning for nodes and relations via heterogeneous graph neural network. Knowl. Based Syst. 255: 109673 (2022) - [j18]Han Han, Can Wang, Yunwei Zhao, Min Shu, Wenlei Wang, Yong Min:
SSLE: A framework for evaluating the "Filter Bubble" effect on the news aggregator and recommenders. World Wide Web 25(3): 1169-1195 (2022) - [c37]Weibin Zhao, Aoran Zhang, Lin Shang, Yonghong Yu, Li Zhang, Can Wang, Jiajun Chen, Hongzhi Yin:
Hyperbolic Personalized Tag Recommendation. DASFAA (2) 2022: 216-231 - 2021
- [j17]Weimin Li, Heng Zhu, Shaohua Li, Hao Wang, Hongning Dai, Can Wang, Qun Jin:
Evolutionary community discovery in dynamic social networks via resistance distance. Expert Syst. Appl. 171: 114536 (2021) - [j16]Can Wang, Fosca Giannotti, Longbing Cao:
Learning Complex Couplings and Interactions. IEEE Intell. Syst. 36(1): 3-5 (2021) - [j15]Wenpeng Lu, Rui Yu, Shoujin Wang, Can Wang, Ping Jian, Heyan Huang:
Sentence Semantic Matching Based on 3D CNN for Human-Robot Language Interaction. ACM Trans. Internet Techn. 21(4): 98:1-98:24 (2021) - [c36]Xuan Cuong Pham, Alan Wee-Chung Liew, Can Wang:
A Novel Class-wise Forgetting Detector in Continual Learning. DICTA 2021: 1-8 - [c35]Tianxing Wang, Can Wang, Hui Tian, Alan Wee-Chung Liew, Yunwei Zhao:
Clustering-based Location Authority Deep Model in the Next Point-of-Interest Recommendation. WI/IAT 2021: 335-342 - [i7]Yun Li, Zhe Liu, Lina Yao, Xianzhi Wang, Can Wang:
Attribute-Modulated Generative Meta Learning for Zero-Shot Classification. CoRR abs/2104.10857 (2021) - 2020
- [j14]Md. Saiful Islam, Bojie Shen, Can Wang, David Taniar, Junhu Wang:
Efficient processing of reverse nearest neighborhood queries in spatial databases. Inf. Syst. 92: 101530 (2020) - [j13]Hui Tian, Wenwen Sheng, Hong Shen, Can Wang:
Truth finding by reliability estimation on inconsistent entities for heterogeneous data sets. Knowl. Based Syst. 187 (2020) - [j12]Weimin Li, Yuting Fan, Jun Mo, Wei Liu, Can Wang, Minjun Xin, Qun Jin:
Three-hop velocity attenuation propagation model for influence maximization in social networks. World Wide Web 23(2): 1261-1273 (2020) - [c34]Ye Tao, Can Wang, Lina Yao, Weimin Li, Yonghong Yu:
TRec: Sequential Recommender Based On Latent Item Trend Information. IJCNN 2020: 1-8 - [c33]Zhe Liu, Lina Yao, Lei Bai, Xianzhi Wang, Can Wang:
Spectrum-Guided Adversarial Disparity Learning. KDD 2020: 114-124 - [c32]Lei Bai, Lina Yao, Can Li, Xianzhi Wang, Can Wang:
Adaptive Graph Convolutional Recurrent Network for Traffic Forecasting. NeurIPS 2020 - [c31]Yunwei Zhao, Can Wang, Han Han, Min Shu, Wenlei Wang:
An Impact Evaluation Framework of Personalized News Aggregation and Recommendation Systems. WI/IAT 2020: 893-900 - [i6]Lei Bai, Lina Yao, Can Li, Xianzhi Wang, Can Wang:
Adaptive Graph Convolutional Recurrent Network for Traffic Forecasting. CoRR abs/2007.02842 (2020) - [i5]Zhe Liu, Lina Yao, Lei Bai, Xianzhi Wang, Can Wang:
Spectrum-Guided Adversarial Disparity Learning. CoRR abs/2007.06831 (2020) - [i4]Ye Tao, Can Wang, Lina Yao, Weimin Li, Yonghong Yu:
TRec: Sequential Recommender Based On Latent Item Trend Information. CoRR abs/2009.05183 (2020)
2010 – 2019
- 2019
- [j11]Yonghong Yu, Li Zhang, Can Wang, Rong Gao, Weibin Zhao, Jing Jiang:
Neural Personalized Ranking via Poisson Factor Model for Item Recommendation. Complex. 2019: 3563674:1-3563674:16 (2019) - [j10]Xiaofeng Zhu, Rongyao Hu, Cong Lei, Kim-Han Thung, Wei Zheng, Can Wang:
Low-rank hypergraph feature selection for multi-output regression. World Wide Web 22(2): 517-531 (2019) - [c30]Han Han, Yunwei Zhao, Can Wang, Min Shu, Tao Peng, Chi-Hung Chi, Yonghong Yu:
A Methodology for Resolving Heterogeneity and Interdependence in Data Analytics. ADMA 2019: 17-33 - [c29]Can Wang, Zhonghao Sun, Yunwei Zhao, Chi-Hung Chi, Willem-Jan van den Heuvel, Kwok-Yan Lam, Bela Stantic:
Top-N Hashtag Prediction via Coupling Social Influence and Homophily. ADMA 2019: 343-358 - [c28]Yunwei Zhao, Can Wang, Han Han, Willem-Jan van den Heuvel, Chi-Hung Chi, Weimin Li:
Unfolding the Mixed and Intertwined: A Multilevel View of Topic Evolution on Twitter. ADMA 2019: 359-369 - [c27]Weitong Chen, Lin Yue, Bohan Li, Can Wang, Quan Z. Sheng:
DAMTRNN: A Delta Attention-Based Multi-task RNN for Intention Recognition. ADMA 2019: 373-388 - [c26]Tao Bo, Yue Chen, Can Wang, Yunwei Zhao, Kwok-Yan Lam, Chi-Hung Chi, Hui Tian:
TOM: A Threat Operating Model for Early Warning of Cyber Security Threats. ADMA 2019: 696-711 - [c25]Guijiang Wang, Jiulei Jiang, Weimin Li, Can Wang:
Influence Maximization Based on Node Attraction Model. DASC/PiCom/DataCom/CyberSciTech 2019: 437-441 - [c24]Yonghong Yu, Qiang Wang, Li Zhang, Can Wang, Sifan Wu, Boyu Qi, Xiaotian Wu:
Integrating Social Circles and Network Representation Learning for Item Recommendation. IJCNN 2019: 1-8 - [c23]Yunwei Zhao, Can Wang, Chi-Hung Chi, Willem-Jan van den Heuvel, Kwok-Yan Lam, Min Shu:
Beyond the Power of Mere Repetition: Forms of Social Communication on Twitter through the Lens of Information Flows and Its Effect on Topic Evolution. IJCNN 2019: 1-8 - 2018
- [j9]Can Wang, Tao Bo, Yunwei Zhao, Chi-Hung Chi, Kwok-Yan Lam, Sen Wang, Min Shu:
Behavior-Interior-Aware User Preference Analysis Based on Social Networks. Complex. 2018: 7371209:1-7371209:18 (2018) - [j8]Can Wang, Chi-Hung Chi, Zhong She, Longbing Cao, Bela Stantic:
Coupled Clustering Ensemble by Exploring Data Interdependence. ACM Trans. Knowl. Discov. Data 12(6): 63:1-63:38 (2018) - [c22]Jake Hashim-Jones, Can Wang, Md. Saiful Islam, Bela Stantic:
Interdependent Model for Point-of-Interest Recommendation via Social Networks. ADC 2018: 161-173 - [c21]Yunwei Zhao, Can Wang, Chi-Hung Chi, Kwok-Yan Lam, Sen Wang:
A Comparative Study of Transactional and Semantic Approaches for Predicting Cascades on Twitter. IJCAI 2018: 1212-1218 - [c20]Xiang Zhang, Lina Yao, Chaoran Huang, Sen Wang, Mingkui Tan, Guodong Long, Can Wang:
Multi-modality Sensor Data Classification with Selective Attention. IJCAI 2018: 3111-3117 - [c19]Ran Liu, Xiang Wang, Can Wang:
A Two-Factor Authentication Scheme based on Negative Databases. SSCI 2018: 1110-1115 - [c18]Yonghong Yu, Can Wang, Li Zhang, Rong Gao, Hua Wang:
Geographical Proximity Boosted Recommendation Algorithms for Real Estate. WISE (2) 2018: 51-66 - [e2]Mohadeseh Ganji, Lida Rashidi, Benjamin C. M. Fung, Can Wang:
Trends and Applications in Knowledge Discovery and Data Mining - PAKDD 2018 Workshops, BDASC, BDM, ML4Cyber, PAISI, DaMEMO, Melbourne, VIC, Australia, June 3, 2018, Revised Selected Papers. Lecture Notes in Computer Science 11154, Springer 2018, ISBN 978-3-030-04502-9 [contents] - [i3]Xiang Zhang, Lina Yao, Chaoran Huang, Sen Wang, Mingkui Tan, Guodong Long, Can Wang:
Multi-modality Sensor Data Classification with Selective Attention. CoRR abs/1804.05493 (2018) - 2017
- [j7]Yonghong Yu, Can Wang, Hao Wang, Yang Gao:
Attributes coupling based matrix factorization for item recommendation. Appl. Intell. 46(3): 521-533 (2017) - [j6]Xiaofeng Zhu, Xuelong Li, Shichao Zhang, Zongben Xu, Litao Yu, Can Wang:
Graph PCA Hashing for Similarity Search. IEEE Trans. Multim. 19(9): 2033-2044 (2017) - 2016
- [j5]Chi-Hung Chi, Can Wang, Yu Zheng:
Special Issue on Trajectory-based Behaviour Analytics. J. Comput. Syst. Sci. 82(4): 565 (2016) - 2015
- [j4]Xin Cheng, Duoqian Miao, Can Wang:
A link-based approach to semantic relation analysis. Neurocomputing 154: 127-138 (2015) - [j3]Can Wang, Xiangjun Dong, Fei Zhou, Longbing Cao, Chi-Hung Chi:
Coupled Attribute Similarity Learning on Categorical Data. IEEE Trans. Neural Networks Learn. Syst. 26(4): 781-797 (2015) - [j2]Can Wang, Longbing Cao, Chi-Hung Chi:
Formalization and Verification of Group Behavior Interactions. IEEE Trans. Syst. Man Cybern. Syst. 45(8): 1109-1124 (2015) - [c17]Yunwei Zhao, Chi-Hung Chi, Chen (Cherie) Ding, Raymond K. Wong, Wei Zhao, Can Wang:
Hierarchical Clustering Using Homogeneity as Similarity Measure for Big Data Analytics. SCC 2015: 348-354 - [c16]Can Wang, Chi-Hung Chi, Wei Zhou, Raymond K. Wong:
Coupled Interdependent Attribute Analysis on Mixed Data. AAAI 2015: 1861-1867 - [i2]Stefano V. Albrecht, J. Christopher Beck, David L. Buckeridge, Adi Botea, Cornelia Caragea, Chi-Hung Chi, Theodoros Damoulas, Bistra Dilkina, Eric Eaton, Pooyan Fazli, Sam Ganzfried, Marius Lindauer, Marlos C. Machado, Yuri Malitsky, Gary Marcus, Sebastiaan A. Meijer, Francesca Rossi, Arash Shaban-Nejad, Sylvie Thiébaux, Manuela M. Veloso, Toby Walsh, Can Wang, Jie Zhang, Yu Zheng:
Reports from the 2015 AAAI Workshop Program. AI Mag. 36(2): 90-101 (2015) - 2014
- [j1]Longbing Cao, Thorsten Joachims, Can Wang, Éric Gaussier, Jinjiu Li, Yuming Ou, Dan Luo, Reza Zafarani, Huan Liu, Guandong Xu, Zhiang Wu, Gabriella Pasi, Ya Zhang, Xiaokang Yang, Hongyuan Zha, Edoardo Serra, V. S. Subrahmanian:
Behavior Informatics: A New Perspective. IEEE Intell. Syst. 29(4): 62-80 (2014) - [c15]Wei Zhou, Chi-Hung Chi, Can Wang, Raymond K. Wong, Chen (Cherie) Ding:
Bridging the Gap between Spatial Data Sources and Mashup Applications. BigData Congress 2014: 554-561 - [i1]Yonghong Yu, Can Wang, Yang Gao:
Attributes Coupling based Item Enhanced Matrix Factorization Technique for Recommender Systems. CoRR abs/1405.0770 (2014) - 2013
- [b1]Can Wang:
Coupled behavior informatics: modeling, analysis and learning. University of Technology Sydney, Australia, 2013 - [c14]Can Wang, Zhong She, Longbing Cao:
Coupled clustering ensemble: Incorporating coupling relationships both between base clusterings and objects. ICDE 2013: 374-385 - [c13]Can Wang, Zhong She, Longbing Cao:
Coupled Attribute Analysis on Numerical Data. IJCAI 2013: 1736-1742 - [c12]Xin Cheng, Duoqian Miao, Can Wang, Longbing Cao:
Coupled term-term relation analysis for document clustering. IJCNN 2013: 1-8 - [c11]Zhong She, Can Wang:
Volatility analysis via coupled Wishart process. IJCNN 2013: 1-8 - [c10]Jinjiu Li, Can Wang, Wei Wei, Mu Li, Chunming Liu:
Efficient Mining of Contrast Patterns on Large Scale Imbalanced Real-Life Data. PAKDD (1) 2013: 62-73 - [c9]Yonghong Yu, Can Wang, Yang Gao, Longbing Cao, Xixi Chen:
A Coupled Clustering Approach for Items Recommendation. PAKDD (2) 2013: 365-376 - [c8]Yonghong Yu, Can Wang, Yang Gao, Longbing Cao, Qianqian Chen:
Erratum: A Coupled Clustering Approach for Items Recommendation. PAKDD (2) 2013 - [c7]Longbing Cao, Jinjiu Li, Can Wang, Philip S. Yu:
Efficient Selection of Globally Optimal Rules on Large Imbalanced Data Based on Rule Coverage Relationship Analysis. SDM 2013: 216-224 - [e1]Jiuyong Li, Longbing Cao, Can Wang, Kay Chen Tan, Bo Liu, Jian Pei, Vincent S. Tseng:
Trends and Applications in Knowledge Discovery and Data Mining - PAKDD 2013 International Workshops: DMApps, DANTH, QIMIE, BDM, CDA, CloudSD, Gold Coast, QLD, Australia, April 14-17, 2013, Revised Selected Papers. Lecture Notes in Computer Science 7867, Springer 2013, ISBN 978-3-642-40318-7 [contents] - 2012
- [c6]Zhong She, Can Wang, Longbing Cao:
CCE: A Coupled Framework of Clustering Ensembles. AAAI 2012: 2455-2456 - [c5]Can Wang, Mingchun Wang, Zhong She, Longbing Cao:
CD: A Coupled Discretization Algorithm. PAKDD (2) 2012: 407-418 - 2011
- [c4]Chayapol Moemeng, Can Wang, Longbing Cao:
Obtaining an Optimal MAS Configuration for Agent-Enhanced Mining Using Constraint Optimization. ADMI 2011: 46-57 - [c3]Can Wang, Longbing Cao, Mingchun Wang, Jinjiu Li, Wei Wei, Yuming Ou:
Coupled nominal similarity in unsupervised learning. CIKM 2011: 973-978 - [c2]Juan Zhao, Mingchun Wang, Kun Liu, Can Wang:
Discretization Based on Positive Domain and Information Entropy. CIS 2011: 258-262 - 2010
- [c1]Jia-Yi Feng, Mingchun Wang, Can Wang, Longbing Cao:
Enhanced co-occurrence distances for categorical data in unsupervised learning. ICMLC 2010: 2071-2078
Coauthor Index
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