计算机技术与发展Issue(12)：88-91,95,5.DOI:10.3969/j.issn.1673-629X.2014.12.021
基于用户-项目的混合协同过滤算法
A Hybrid Collaborative Filtering Algorithm Based on User-item
摘要
Abstract
According to the problems such as cold start,sparse data existed in the traditional collaborative filtering algorithms,a hybrid collaborative filtering algorithm is proposed which combines user-based and item-based collaborative filtering.An improved algorithm is proposed to improve the accuracy of similarity calculation in the similarity algorithm.The control factors and balance factors are intro-duced in the missing data prediction process for the finally comprehensive recommendation.MovieLens dataset is applied in the experi-ments,the mean absolute error is used for the experiment as a test standard.Experimental results show that the user-item hybrid collabora-tive filtering algorithm can improve the recommendation performance and prediction accuracy in the extremely sparse matrix.关键词
协同过滤/推荐/未评分值预测/冷启动/数据稀疏Key words
collaborative filtering/recommendation/missing data prediction/cold start/sparse data分类
信息技术与安全科学引用本文复制引用
陈彦萍,王赛..基于用户-项目的混合协同过滤算法[J].计算机技术与发展,2014,(12):88-91,95,5.基金项目
陕西省自然科学基金资助项目（2012JQ8029）；陕西省教育科研计划资助项目 （）
