现代信息科技2024，Vol.8Issue(24)：49-53,5.DOI:10.19850/j.cnki.2096-4706.2024.24.011
基于用户特征与信任度的协同过滤推荐算法
Collaborative Filtering Recommendation Algorithm Based on User Characteristics and Trust
摘要
Abstract
Aiming at the problems of cold boot and low recommendation accuracy of the traditional Collaborative Filtering algorithm,a Recommendation Algorithm Based on User Characteristics and Trust(RA-UCT)is proposed.The algorithm firstly uses the user's demographic information and rating data to calculate the feature similarity.Then,based on the improved similarity,it constructs a user trust network,calculates the comprehensive trust,and makes recommendations based on the two dimensions of feature similarity and comprehensive trust.The experimental results on the MovieLens public dataset show that compared with the traditional Collaborative Filtering method,the proposed algorithm can effectively improve the recommendation accuracy and effectively alleviate the cold boot problem.关键词
属性特征/信任度/协同过滤/冷启动Key words
attribute characteristics/trust/Collaborative Filtering/cold boot分类
信息技术与安全科学引用本文复制引用
李彭..基于用户特征与信任度的协同过滤推荐算法[J].现代信息科技,2024,8(24):49-53,5.
