Reinforced Path Reasoning for Counterfactual Explainable Recommendation
Xiangmeng Wang, Qian Li, Dianer Yu, Guandong Xu

TL;DR
This paper introduces CERec, a reinforcement learning-based method for generating item attribute-based counterfactual explanations that improve recommendation quality by efficiently exploring minimal item attribute changes.
Contribution
It proposes a novel adaptive path sampling and explanation policy to generate intuitive counterfactual explanations and enhance recommendation performance.
Findings
CERec provides explanations aligned with user preferences.
CERec improves recommendation accuracy and relevance.
The method effectively reduces search space for counterfactuals.
Abstract
Counterfactual explanations interpret the recommendation mechanism via exploring how minimal alterations on items or users affect the recommendation decisions. Existing counterfactual explainable approaches face huge search space and their explanations are either action-based (e.g., user click) or aspect-based (i.e., item description). We believe item attribute-based explanations are more intuitive and persuadable for users since they explain by fine-grained item demographic features (e.g., brand). Moreover, counterfactual explanation could enhance recommendations by filtering out negative items. In this work, we propose a novel Counterfactual Explainable Recommendation (CERec) to generate item attribute-based counterfactual explanations meanwhile to boost recommendation performance. Our CERec optimizes an explanation policy upon uniformly searching candidate counterfactuals within a…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Code & Models
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsRecommender Systems and Techniques · Explainable Artificial Intelligence (XAI) · Topic Modeling
MethodsCounterfactuals Explanations
