480 citations · 960 across the 4 of their papers we have counts for
Showing cs.IRShow all
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cs.IR2018★ 463 cited
Learning Heterogeneous Knowledge Base Embeddings for Explainable Recommendation
Qingyao Ai, Vahid Azizi, Xu Chen +1
Providing model-generated explanations in recommender systems is important to user experience. State-of-the-art recommendation algorithms - especially collaborative filtering (CF)-…
cs.IR2018★ 480 cited
Learning over Knowledge-Base Embeddings for Recommendation
Yongfeng Zhang, Qingyao Ai, Xu Chen +1
State-of-the-art recommendation algorithms -- especially the collaborative filtering (CF) based approaches with shallow or deep models -- usually work with various unstructured inf…