Time-aware Path Reasoning on Knowledge Graph for Recommendation

TL;DR

This paper introduces TPRec, a time-aware path reasoning method for knowledge graph-based recommendation systems that incorporates temporal information to improve recommendation accuracy and explanation quality.

Contribution

It proposes a novel time-aware path reasoning approach and constructs a temporal knowledge graph to enhance explainable recommendations.

Findings

TPRec outperforms baseline methods on three real-world datasets.

Incorporating temporal information improves recommendation relevance.

The method provides more plausible and accurate explanations.

Abstract

Reasoning on knowledge graph (KG) has been studied for explainable recommendation due to it's 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 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.