2 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…