370 citations · 1.8k across the 232 of their papers we have counts for
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cs.IR2024
InBox: Recommendation with Knowledge Graph using Interest Box Embedding
Zezhong Xu, Yincen Qu, Wen Zhang +2
Knowledge graphs (KGs) have become vitally important in modern recommender systems, effectively improving performance and interpretability. Fundamentally, recommender systems aim t…
cs.IR2021★ 2 cited
Improving Conversational Recommendation System by Pretraining on Billions Scale of Knowledge Graph
Chi-Man Wong, Fan Feng, Wen Zhang +7
Conversational Recommender Systems (CRSs) in E-commerce platforms aim to recommend items to users via multiple conversational interactions. Click-through rate (CTR) prediction mode…
cs.IR2019★ 7 cited
Long-tail Relation Extraction via Knowledge Graph Embeddings and Graph Convolution Networks
Ningyu Zhang, Shumin Deng, Zhanlin Sun +4
We propose a distance supervised relation extraction approach for long-tailed, imbalanced data which is prevalent in real-world settings. Here, the challenge is to learn accurate "…