知识图谱的推荐系统综述

如何为用户提供个性化推荐并提高推荐的准确度和用户满意度，是当前推荐系统研究面临的主要问题。知识图谱的出现为推荐系统的改进提供了新的途径。本文研究了知识图谱近年来在推荐系统中的应用情况，从基于本体的推荐生成、基于开放链接数据的推荐生成以及基于图嵌入的推荐生成3个方面对研究现状进行了综述。在此基础上，提出了基于知识图谱的推荐系统总体框架，分析了其中涉及的关键技术，并对目前存在的重点和难点问题进行了讨论，指出了下一步需要开展的研究工作。

Review of recommendation systems based on knowledge graph

In current research on recommendation systems, the provision of personalized recommendations to users and the improvement of the accuracy and user satisfaction of recommendations are main concerns. The emergence of knowledge graphs provides a new way to improve recommendation systems. The applications of knowledge graphs to recommendation systems in recent years are summarized in this paper, and the current status of the research is investigated in detail from three aspects:ontology-based recommendation generation, recommendation generation based on linked open data, and recommendation generation based on graph embedding. On this basis, this paper proposes the general framework of recommendation systems based on knowledge graph, analyzes the key technologies involved, discusses the existing key issues and difficulties, and indicates the further research work to be carried out.