Analyzing the evolution map of traditional personalized recommendation model and the evolution map of personalized recommendation model based on deep learning is of great significance to sort out the development context of personalized recommendation technology. This study used CiteSpace 6.1.R2 software to analyze Chinese literature on "personalized recommendation" retrieved from China National Knowledge Infrastructure (CNKI) from 2002 to 2022,as well as relevant literature on "personalized recommendation al-gorithms and data risks" from 2005 to 2022. The study identified hot topics and future development trends in the field of personalized recommendation,and proposed regulatory measures for data risks and prevention of personalized recommendation algorithms.
维普
万方数据