Intelligent recommendation method of literature reading based on user social network analysis
Qiaohua Han · 2020
In order to recommend literary works of interest to readers and improve readers' reading efficiency, an intelligent recommendation method for literary reading based on user social network analysis is proposed. The intelligent recommendation model for personalized resource services is optimized for the intelligent recommendation engine. Collect readers' reading interest data sources, based on this, divide the reader's knowledge level, reading behavior, reading style, and reading interest into reading resource recommendation directions, improve the intelligent recommendation engine, personalized service and other modules, so as to comprehensively analyze the attributes of reading resources, Type, efficiency and evolution to realize rapid retrieval, matching, management and recommendation of literary reading. The simulation results show that the recommended error of literature reading of this method is small, and user satisfaction is improved.