基于CiteSpace的推荐系统文献计量与可视化分析

Bibliometric and Visual Analysis of Recommendation System Based on CiteSpace

为深入探讨推荐系统研究现状及其发展趋势,本文使用文献计量学的方法,使用CiteSpace可视化软件对推荐系统领域的研究现状进行了深入讨论,揭示了该领域的研究现状、热点和前沿趋势。本文从CNKI和WOS数据库中选取了2000年至2023年发表的3 168篇中文期刊论文和12 517篇英文期刊论文,对研究作者、研究机构以及关键词等进行可视化分析。通过对共同引用的分析确定了该领域的重要知识库,并采用双标图叠加分析法探讨了学科间的知识流动。通过对科学可视化知识图谱的解读,得出推荐系统的研究趋势主要集中在机器学习、数据挖掘和信息检索等议题。

In order to further explore the research status and development trend of recommendation system,this paper uses the method of bibliometrics and CiteSpace visualization software to conduct in-depth research on the research status of recommendation system,revealing the research status,hot spots and frontier trends in this field.From 2000 to 2023,3,168 Chinese journal papers and 12,517 English journal papers were selected from CNKI and WOS databases for visual analysis of study authors,research institutions and key words.The important knowledge base in this field is determined by the analysis of common reference,and the knowledge flow between disciplines is discussed by the method of double plot superposition.Through the interpretation of scientific visual knowledge graph,it is concluded that the research trend of recommendation system mainly focuses on machine learning,data mining and information retrieval.