13 citations · 18 across the 4 of their papers we have counts for
4 papers · 1 filter
REASONER: An Explainable Recommendation Dataset with Multi-aspect Real User Labeled Ground Truths Towards more Measurable Explainable Recommendation
Xu Chen, Jingsen Zhang, Lei Wang +6
Explainable recommendation has attracted much attention from the industry and academic communities. It has shown great potential for improving the recommendation persuasiveness, in…
RecBole 2.0: Towards a More Up-to-Date Recommendation Library
Wayne Xin Zhao, Yupeng Hou, Xingyu Pan +16
In order to support the study of recent advances in recommender systems, this paper presents an extended recommendation library consisting of eight packages for up-to-date topics a…
Sequential Recommendation with Causal Behavior Discovery
Zhenlei Wang, Xu Chen, Rui Zhou +3
The key of sequential recommendation lies in the accurate item correlation modeling. Previous models infer such information based on item co-occurrences, which may fail to capture…
Measuring "Why" in Recommender Systems: a Comprehensive Survey on the Evaluation of Explainable Recommendation
Xu Chen, Yongfeng Zhang, Ji-Rong Wen
Explainable recommendation has shown its great advantages for improving recommendation persuasiveness, user satisfaction, system transparency, among others. A fundamental problem o…