Sequential Recommendation with Collaborative Explanation via Mutual Information Maximization - Lecture 1

Explore a cutting-edge approach to sequential recommendation systems in this 19-minute conference talk from SIGIR 2024. Delve into the innovative method of collaborative explanation through mutual information maximization, presented by researchers Yi Yu, Kazunari Sugiyama, and Adam Jatowt. Gain insights into how this technique enhances explainability in search and recommendation systems, potentially revolutionizing user experience and system transparency. Learn about the intersection of sequential recommendation, collaborative filtering, and information theory in this concise yet informative presentation from the Association for Computing Machinery (ACM).

SIGIR 2024 T1.1 [fp] Sequential Rec Collaboration Explanation via Mutual Info Maximization