Research on Personalized Recommendation Service of Mobile Library Based on User Portrait

Embedding user portraits into the personalized recommendation service of mobile libraries will solve the problems of information overload and semantic gap, and the retrieval results cannot meet the personalized needs of readers. Based on user portrait technology, the mobile library’s recommendation service has built a personalized recommendation service model through the processes of data collection, data preprocessing, portrait modeling and effect evaluation. It analyzes the key issues involved in user privacy protection, dynamic changes in user portraits, and service performance optimization.