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cs.IR2022
Coarse-to-Fine Sparse Sequential Recommendation
Jiacheng Li, Tong Zhao, Jin Li +5
Sequential recommendation aims to model dynamic user behavior from historical interactions. Self-attentive methods have proven effective at capturing short-term dynamics and long-t…
cs.IR2022
Learning Personalized Item-to-Item Recommendation Metric via Implicit Feedback
Trong Nghia Hoang, Anoop Deoras, Tong Zhao +2
This paper studies the item-to-item recommendation problem in recommender systems from a new perspective of metric learning via implicit feedback. We develop and investigate a pers…