3 papers
cs.IR2026
Bridging Textual Profiles and Latent User Embeddings for Personalization
Zhaoxuan Tan, Xiang Zhai, Yan Zhu +2
Personalized systems rely on user representations to connect behavioral history with downstream recommendation applications. Existing methods typically employ either supervised lat…
cs.IR2025
Interest Changes: Considering User Interest Life Cycle in Recommendation System
Yinjiang Cai, Jiangpan Hou, Yangping Zhu +1
In recommendation systems, user interests are always in a state of constant flux. Typically, a user interest experiences a emergent phase, a stable phase, and a declining phase, wh…
cs.IR2024
RimiRec: Modeling Refined Multi-interest in Hierarchical Structure for Recommendation
Haolei Pei, Yuanyuan Xu, Yangping Zhu +1
Industrial recommender systems usually consist of the retrieval stage and the ranking stage, to handle the billion-scale of users and items. The retrieval stage retrieves candidate…