计算机应用研究2016，Vol.33Issue(11)：3329-3333,5.DOI:10.3969/j.issn.1001--3695.2016.11.029
基于用户引力的协同过滤推荐算法
Collaborative filtering recommendation algorithm based on user’s gravitation
王国霞1
作者信息
- 1. 北京科技大学 自动化学院，北京 100083
- 折叠
摘要
Abstract
There are some shortcomings in user-based collaborative filtering,this paper proposed a new collaborative filtering recommendation algorithms,named user’s gravitation based collaborative filtering (UGBCF)recommendation algorithm,it used a new method of similarity measure to improve the user-based collaborative recommendation algorithms.This paper thought that the social tags used by user can reflect user’s preference and how much the preference,so it used those social tags to build user’s preference object model.It computed the gravitation between preference objects,viewed the gravitation as the similarity of users.According to the similarity,the neighbor user of the target user could be gotten,and the prediction score of his unselected items could be calculated by aggregated the neighbor users’score.The results of experiment show that UGBCF can provide better recommendation quality than other collaborative filtering recommendation.关键词
推荐算法/协同过滤推荐/万有引力定律/社会标签Key words
recommendation algorithms/collaborative filtering/universal law of gravitation/social tag分类
信息技术与安全科学引用本文复制引用
王国霞..基于用户引力的协同过滤推荐算法[J].计算机应用研究,2016,33(11):3329-3333,5.
