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cs.IR2025
Unified Representation Learning for Multi-Intent Diversity and Behavioral Uncertainty in Recommender Systems
Wei Xu, Jiasen Zheng, Junjiang Lin +2
This paper addresses the challenge of jointly modeling user intent diversity and behavioral uncertainty in recommender systems. A unified representation learning framework is propo…
cs.IR2025
Modeling Multi-Hop Semantic Paths for Recommendation in Heterogeneous Information Networks
Hongye Zheng, Yue Xing, Lipeng Zhu +3
This study focuses on the problem of path modeling in heterogeneous information networks and proposes a multi-hop path-aware recommendation framework. The method centers on multi-h…