96 citations · 143 across the 8 of their papers we have counts for
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cs.IR2021
Path-based Deep Network for Candidate Item Matching in Recommenders
Houyi Li, Zhihong Chen, Chenliang Li +5
The large-scale recommender system mainly consists of two stages: matching and ranking. The matching stage (also known as the retrieval step) identifies a small fraction of relevan…
cs.IR2020★ 96 cited
ESAM: Discriminative Domain Adaptation with Non-Displayed Items to Improve Long-Tail Performance
Zhihong Chen, Rong Xiao, Chenliang Li +3
Most of ranking models are trained only with displayed items (most are hot items), but they are utilized to retrieve items in the entire space which consists of both displayed and…