Explore a 13-minute conference presentation from SIGIR 2024 that delves into treatment effect estimation methods for understanding user interest exploration in recommender systems. Learn from researchers Jiaju Chen, Wenjie Wang, Chongming Gao, Peng Wu, Jianxiong Wei, and Qingsong Hua as they present their findings on long-term and session-based recommendation techniques. Gain insights into how treatment effects can be measured and utilized to better understand user behavior and improve recommendation system performance.
Treatment Effect Estimation for User Interest Exploration on Recommender Systems
Association for Computing Machinery (ACM) via YouTube
Overview
Syllabus
SIGIR 2024 W1.2 [fp] Treatment Effect Estimation for User Interest Exploration on RecSys
Taught by
Association for Computing Machinery (ACM)
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