3 citations · 4 across the 2 of their papers we have counts for
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cs.IR2022★ 1 cited
Addressing the Extreme Cold-Start Problem in Group Recommendation
Guo linxin, Tao yinghui, Gao Min +3
The task of recommending items to a group of users, a.k.a. group recommendation, is receiving increasing attention. However, the cold-start problem inherent in recommender systems…
cs.IR2022★ 3 cited
Efficient Bi-Level Optimization for Recommendation Denoising
Zongwei Wang, Min Gao, Wentao Li +3
The acquisition of explicit user feedback (e.g., ratings) in real-world recommender systems is often hindered by the need for active user involvement. To mitigate this issue, impli…