Neuro-Symbolic Interpretable Collaborative Filtering for Attribute-based Recommendation
Wei Zhang, Junbing Yan, Zhuo Wang, Jianyong Wang · Proceedings of the ACM Web Conference 2022 · 2022
Recommender System (RS) is ubiquitous on today’s Internet to provide multifaceted personalized information services. While an enormous success has been made in pushing forward high-accuracy recommendations, the other side of the coin — the recommendation explainability — needs to be better handled for pursuing persuasiveness, especially for the era of deep learning based recommendation. A few research efforts investigate interpretable recommendation from the feature and result levels. Compared with them, model-level explanation, which unfolds the reasoning process of recommendation through transparent models, still remains underexplored and deserves more attention.