1 citations · 2 across the 3 of their papers we have counts for
3 papers
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.CL2022★ 1 cited
Commonsense Knowledge Salience Evaluation with a Benchmark Dataset in E-commerce
Yincen Qu, Ningyu Zhang, Hui Chen +6
In e-commerce, the salience of commonsense knowledge (CSK) is beneficial for widespread applications such as product search and recommendation. For example, when users search for `…
cs.CL2022★ 1 cited
SQUIRE: A Sequence-to-sequence Framework for Multi-hop Knowledge Graph Reasoning
Yushi Bai, Xin Lv, Juanzi Li +4
Multi-hop knowledge graph (KG) reasoning has been widely studied in recent years to provide interpretable predictions on missing links with evidential paths. Most previous works us…