142 citations · 570 across the 47 of their papers we have counts for
Showing 2021 · cs.IRShow all
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cs.IR2021★ 1 cited
PURS: Personalized Unexpected Recommender System for Improving User Satisfaction
Pan Li, Maofei Que, Zhichao Jiang +2
Classical recommender system methods typically face the filter bubble problem when users only receive recommendations of their familiar items, making them bored and dissatisfied. T…
cs.IR2021
Dual Attentive Sequential Learning for Cross-Domain Click-Through Rate Prediction
Pan Li, Zhichao Jiang, Maofei Que +2
Cross domain recommender system constitutes a powerful method to tackle the cold-start and sparsity problem by aggregating and transferring user preferences across multiple categor…
cs.IR2021★ 14 cited
Dual Metric Learning for Effective and Efficient Cross-Domain Recommendations
Pan Li, Alexander Tuzhilin
Cross domain recommender systems have been increasingly valuable for helping consumers identify useful items in different applications. However, existing cross-domain models typica…