A survey of research hotspots and frontier trends of recommendation systems from the perspective of knowledge graph

作者：

Highlights：

• Revealing research hotspot and corresponding characteristics by bibliometric methods.

• Discovering underlying laws behind data by constructing scientific knowledge graph.

• Summarizing potential research hotspots by keyword co-occurrence cluster graph.

• Summarizing cutting-edge trends by keyword co-occurrence cluster graph.

• Discussing the main open problems in depth and proposing corresponding solutions.

摘要

•Revealing research hotspot and corresponding characteristics by bibliometric methods.•Discovering underlying laws behind data by constructing scientific knowledge graph.•Summarizing potential research hotspots by keyword co-occurrence cluster graph.•Summarizing cutting-edge trends by keyword co-occurrence cluster graph.•Discussing the main open problems in depth and proposing corresponding solutions.

论文关键词：Recommendation system,Knowledge graph,Collaborative filtering,Personalization,User modeling

论文评审过程：Received 15 September 2019, Revised 28 June 2020, Accepted 14 July 2020, Available online 19 July 2020, Version of Record 4 September 2020.

论文官网地址：https://doi.org/10.1016/j.eswa.2020.113764