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ORCID28th PAKDD 2024: Taipei, Taiwan - Workshops
- Zhaoxia Wang
, Chang Wei Tan:
Trends and Applications in Knowledge Discovery and Data Mining - PAKDD 2024 Workshops, RAFDA and IWTA, Taipei, Taiwan, May 7-10, 2024, Proceedings. Lecture Notes in Computer Science 14658, Springer 2024, ISBN 978-981-97-2649-3
PAKDD 2024 workshop on Research and Applications of Foundation Models for Data Mining and Affective Computing (RAFDA 2024)
- Donghao Huang, Zhaoxia Wang:
Evaluation of Orca 2 Against Other LLMs for Retrieval Augmented Generation. 3-19 - Tien-Cuong Bui, Wen-Syan Li:
Toward Interpretable Graph Classification via Concept-Focused Structural Correspondence. 20-31 - Saketh Reddy Karra, Theja Tulabandhula:
InteraRec: Interactive Recommendations Using Multimodal Large Language Models. 32-43 - Kui Hu, Zhenyu Zhang, Xiaoming Li:
Research on Dynamic Community Detection Method Based on Multi-dimensional Feature Information of Community Network. 44-56 - Donghao Huang, Samuel Samuel, Quoc Toan Hyunh, Zhaoxia Wang:
From Tweets to Token Sales: Assessing ICO Success Through Social Media Sentiments. 57-69 - Yongxin Chao, Kai Zheng:
Enhanced Graph Neural Network for Session-Based Recommendation with Static and Dynamic Information. 70-81 - Cheng Wei, Cong Tianshi:
Construction of Academic Innovation Chain Based on Multi-level Clustering of Field Literature. 82-94 - Nicole Anne Teo Huiying, Zhaoxia Wang, Ezekiel En Zhe Ghe, Yee Sen Tan, Kevan Oktavio, Alexander Vincent Lewi, Allyne Zhang, Seng-Beng Ho:
DLVS4Audio2Sheet: Deep Learning-Based Vocal Separation for Audio into Music Sheet Conversion. 95-107 - Erik Cambria, Balázs Gulyás, Joyce S. Pang, Nigel V. Marsh, Mythily Subramaniam:
Explainable AI for Stress and Depression Detection in the Cyberspace and Beyond. 108-120
International Workshop on Temporal Analytics (IWTA 2024)
- Ali Ismail-Fawaz, Maxime Devanne, Stefano Berretti, Jonathan Weber, Germain Forestier:
Finding Foundation Models for Time Series Classification with a PreText Task. 123-135 - Jun-Hong Cai, Yi-Hang Tsai, Chia-Ming Chang, San-Yih Hwang:
Next Item and Interval Prediction of New Users Using Meta-Learning on Dynamic Network. 136-147 - Yu-Hsiang Chang, Lo Pang-Yun Ting, Wei-Cheng Yin, Ko-Wei Su, Kun-Ta Chuang:
Adaptive Knowledge Sharing in Multi-Task Learning: Insights from Electricity Data Analysis. 148-160 - Yun-Da Tsai, Shou-De Lin:
Handling Concept Drift in Non-stationary Bandit Through Predicting Future Rewards. 161-173
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