7 citations · 15 across the 4 of their papers we have counts for
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cs.IR2022
Mitigating Frequency Bias in Next-Basket Recommendation via Deconfounders
Xiaohan Li, Zheng Liu, Luyi Ma +4
Recent studies on Next-basket Recommendation (NBR) have achieved much progress by leveraging Personalized Item Frequency (PIF) as one of the main features, which measures the frequ…
cs.IR2021★ 2 cited
Dynamic Graph Collaborative Filtering
Xiaohan Li, Mengqi Zhang, Shu Wu +3
Dynamic recommendation is essential for modern recommender systems to provide real-time predictions based on sequential data. In real-world scenarios, the popularity of items and i…
cs.IR2020
Basket Recommendation with Multi-Intent Translation Graph Neural Network
Zhiwei Liu, Xiaohan Li, Ziwei Fan +3
The problem of basket recommendation~(BR) is to recommend a ranking list of items to the current basket. Existing methods solve this problem by assuming the items within the same b…