Research hotspots and visualization analysis of the domestic e-commerce recommendation system
The research of the e-commerce recommendation system primarily covers areas such as recommendation algorithms,user behavior analysis,personalized recommendation,and recommendation system evaluation.However,current studies mainly focus on specific technologies or application scenarios,lacking a construction and systematic review of the overall research framework.Using CiteSpace software,a visualisation analysis of relevant research from 2001 to 2023 was conducted.The results show that the number of relevant research literature has exhibited an upward trend followed by a decline over the past 23 years and that the cooperation among authors in this research field is relatively loose while that among core authors is much closer,but the connections among major publishing institutions are not close enough.In addition,the research frontiers are concentrated on big data,product recommendation,and clustering,and the research hotspots can be categorized into three main areas:recommendation algorithms and technology,consumer trust,and personalized recommendation,which focus on 11 themes such as e-commerce,collaborative filtering,and the recommendation system.However,at present,the e-commerce recommendation system still faces certain limitations.With ongoing optimization and technological innovation,the future e-commerce recommendation system will become increasingly intelligent,personalized and user-friendly,thereby providing consumers with higher quality service.
NETL
NSTL
万方数据
