Litcius/Paper detail

Time-aware Path Reasoning on Knowledge Graph for Recommendation

Yuyue Zhao, Xiang Wang, Jiawei Chen, Yashen Wang, Wei Tang, Xiangnan He, Haiyong Xie

2022ACM Transactions on Information Systems69 citationsDOIOpen Access PDF

Abstract

Reasoning on knowledge graph (KG) has been studied for explainable recommendation due to its ability of providing explicit explanations. However, current KG-based explainable recommendation methods unfortunately ignore the temporal information (such as purchase time, recommend time, etc.), which may result in unsuitable explanations. In this work, we propose a novel Time-aware Path reasoning for Recommendation (TPRec for short) method, which leverages the potential of temporal information to offer better recommendation with plausible explanations. First, we present an efficient time-aware interaction relation extraction component to construct collaborative knowledge graph with time-aware interactions (TCKG for short), and then we introduce a novel time-aware path reasoning method for recommendation. We conduct extensive experiments on three real-world datasets. The results demonstrate that the proposed TPRec could successfully employ TCKG to achieve substantial gains and improve the quality of explainable recommendation.

Topics & Concepts

Knowledge graphComputer sciencePath (computing)GraphData scienceArtificial intelligenceTheoretical computer scienceProgramming languageAdvanced Graph Neural NetworksRecommender Systems and TechniquesTopic Modeling