Time-aware Path Reasoning on Knowledge Graph for Recommendation

Yuyue Zhao

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 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.