计算机应用研究2017，Vol.34Issue(4)：1022-1025,1031,5.DOI:10.3969/j.issn.1001-3695.2017.04.015
基于标签的矩阵分解推荐算法
Tag-based matrix factorization recommendation algorithm
摘要
Abstract
Tag-based recommendation algorithms have become a hot research topic.Existing related research used tags to improve collaborative-filtering recommendation algorithms or content-based recommendation algorithms,few researchers used tags to improve matrix factorization recommendation algorithm which was one kind of more advanced recommendation algorithm.However,existing matrix factorization recommendation algorithm mainly used commodities' types to model users' preferences or commodities' characteristics,which would limit its improvement in prediction accuracy.This paper made use of tags to build factor vector,and proposed a novel tag-based matrix factorization recommendation algorithm.Results of experiments on real data sets demonstrate the proposed recommendation algorithm performs much better than traditional type-based matrix factorization recommendation algorithm.关键词
标签/矩阵分解/推荐算法/因子向量Key words
tag/matrix factorization/recommendation algorithm/factor vector分类
信息技术与安全科学引用本文复制引用
方冰,牛晓婷..基于标签的矩阵分解推荐算法[J].计算机应用研究,2017,34(4):1022-1025,1031,5.基金项目
上海高校青年教师培养计划资助项目(N.37-0129-15-201) （N.37-0129-15-201）
上海市自然科学基金资助项目(16ZR1447100) （16ZR1447100）
