基于用户聚类的图书推荐算法设计与实现

Design and implementation of book recommendation algorithm based on user clustering

个性化推荐算法中一直存在新用户的冷启动问题,文章通过引入ID3算法来预测、分析新用户的类别选择。首先,根据实验数据特征对ID3算法加以改进;其次,根据分析数据表中各字段的属性确定试验参数;最后,得出实验结果。

There has always been the cold start problem of new users in personalized recommendation algorithm.This paper analyzes the category selection of new users by introducing ID3 algorithm to predict and analyze the category selection of new users.Firstly,the ID3 algorithm is improved according to the characteristics of the experimental data.Secondly,the experimental parameters are determined according to the attributes of each field in the analysis data table.Finally,the experimental results are obtained.