CHANG Liang,ZHANG Weitao,GU Tianlong,et al.Review of recommendation systems based on knowledge graph[J].CAAI Transactions on Intelligent Systems,2019,14(2):207-216.[doi:10.11992/tis.201805001]





Review of recommendation systems based on knowledge graph
常亮 张伟涛 古天龙 孙文平 宾辰忠
桂林电子科技大学 广西可信软件重点实验室, 广西 桂林 541004
CHANG Liang ZHANG Weitao GU Tianlong SUN Wenping BIN Chenzhong
Guangxi Key Laboratory of Trusted Software, Guilin University of Electronic Technology, Guilin 541004, China
knowledge graphrecommendation systemontologylinked open datagraph embeddingnetwork representation learningsimilarityprediction score
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.


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更新日期/Last Update: 2019-04-25