Donghua University - Research on interpretable recommendation micro behavior with enhanced knowledge perception reasoning

【 title 】Micro-behaviour with Reinforcement Knowledge-aware Reasoning for Explainable Recommendation

【 The author team 】Shaohua Tao, Runhe Qiu, Bo Xu, Yuan Ping

【 Date of publication 】2022.6.20

【 Thesis link 】https://www.sciencedirect.com/science/article/pii/S0950705122006529

【 Recommended reasons 】 Some recommendation methods have incorporated project knowledge into the micro behavior of user project interaction . Although some methods have proved effective , But two ideas are often overlooked . First , There is no relationship between micro behavior and knowledge map (KG) The relationship between , The semantic relationship between micro behavior and relationship is not captured . secondly , There is no explicit reasoning for micro behavior from user project interaction data . These insights prompted this paper to propose a novel micro behavior model , That is to say, knowledge aware reasoning can explain recommendation (MBKR) , The model combines micro behavior with KG Combined with reinforcement learning to make interpretable recommendations . say concretely , The model propagates and through user items KG Relationship to learn user behavior , And combine the two to calculate the behavior intensity of mining user interest . Besides , This paper also designs a Shawo Relationship path , Combine recommendation and interpretability by providing a reasonable path ; These paths capture the semantics of behavior and relationships . Last , This paper has extensively evaluated this method on several large benchmark data sets .