Invited lecturer : Wang Wenjie , a researcher at the National University of Singapore, whose main research directions are recommendation systems, causal reasoning and multimodal computing. In 2023, he will receive a Ph.D. from the National University of Singapore under the tutelage of Prof. Chua Tat-Seng. He has published several first-authored papers in high-level conferences and journals such as SIGIR, KDD, WWW, WSDM, ACMMM and TOIS, and served as a reviewer for conferences and journals such as SIGIR, WWW, TPAMI, TOIS, etc. He has obtained 4 national invention patents , whose work has won the best paper candidate of ACM MM 2019. He has won honors such as Google PhD Scholarship, NUS Dean's Scholarship, and NUS Research Achievement Award.
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In today's information age, the recommendation system has become a key infrastructure for users to obtain information, affecting people's understanding and cognition of society. Although the recommendation system has achieved extensive development in recent years, the existing recommendation services have shown a trend of disordered growth, resulting in problems such as recommendation deviation, information cocoons, and poor generalization capabilities, which affect the normal order of information dissemination. In response to these problems, we analyzed the underlying mechanism from the perspective of causality, and proposed a causal recommendation framework based on causal knowledge, using causal reasoning to empower the recommendation system. This report focuses on our series of work in the field of causal recommendation in recent years, and discusses the future development trend of this field.
Syllabus:
1. Background overview of recommender systems and causal reasoning
2. Causal recommendation framework
3. Recent technological developments in causal recommender systems
4. Future research directions in causal recommender systems
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