Reinforcement knowledge graph reasoning for explainable recommendation

Yikun Xian, Zuohui Fu, S. Muthukrishnan, Gerard De Melo, Yongfeng Zhang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

66 Scopus citations

Abstract

Recent advances in personalized recommendation have sparked great interest in the exploitation of rich structured information provided by knowledge graphs. Unlike most existing approaches that only focus on leveraging knowledge graphs for more accurate recommendation, we perform explicit reasoning with knowledge for decision making so that the recommendations are generated and supported by an interpretable causal inference procedure. To this end, we propose a method called Policy-Guided Path Reasoning (PGPR), which couples recommendation and interpretability by providing actual paths in a knowledge graph. Our contributions include four aspects. We first highlight the significance of incorporating knowledge graphs into recommendation to formally define and interpret the reasoning process. Second, we propose a reinforcement learning (RL) approach featuring an innovative soft reward strategy, user-conditional action pruning and a multi-hop scoring function. Third, we design a policy-guided graph search algorithm to efficiently and effectively sample reasoning paths for recommendation. Finally, we extensively evaluate our method on several large-scale real-world benchmark datasets, obtaining favorable results compared with state-of-the-art methods.

Original languageEnglish (US)
Title of host publicationSIGIR 2019 - Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval
PublisherAssociation for Computing Machinery, Inc
Pages285-294
Number of pages10
ISBN (Electronic)9781450361729
DOIs
StatePublished - Jul 18 2019
Event42nd International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2019 - Paris, France
Duration: Jul 21 2019Jul 25 2019

Publication series

NameSIGIR 2019 - Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval

Conference

Conference42nd International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2019
Country/TerritoryFrance
CityParis
Period7/21/197/25/19

All Science Journal Classification (ASJC) codes

  • Information Systems
  • Applied Mathematics
  • Software

Keywords

  • Explainability
  • Knowledge Graphs
  • Recommendation System
  • Reinforcement Learning

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