Zobrazeno 1 - 4
of 4
pro vyhledávání: '"Qu, Yincen"'
Knowledge graphs (KGs) have become vitally important in modern recommender systems, effectively improving performance and interpretability. Fundamentally, recommender systems aim to identify user interests based on historical interactions and recomme
Externí odkaz:
http://arxiv.org/abs/2403.12649
Autor:
Qu, Yincen, Zhang, Ningyu, Chen, Hui, Dai, Zelin, Xu, Zezhong, Wang, Chengming, Wang, Xiaoyu, Chen, Qiang, Chen, Huajun
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 ``running'' in e-commerce, they would like to find products highly rela
Externí odkaz:
http://arxiv.org/abs/2205.10843
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 use reinforcement learning (RL) based methods that learn to navigate the
Externí odkaz:
http://arxiv.org/abs/2201.06206
Publikováno v:
Findings of the Association for Computational Linguistics: ACL 2022.