计算机应用研究2017，Vol.34Issue(2)：339-342,4.DOI:10.3969/j.issn.1001-3695.2017.02.004
基于高阶偏差的因子分解机推荐算法
High-order biased factorization machine recommender algorithm
摘要
Abstract
In recommender system,bias problem caused by different rating scales has always effected the predict precision of collaborative filtering.Concerning this bias problem of matrix factorization,this paper proposed a high-order biased factorization machine recommender algorithm.Firstly,it grouped users and items by their rating bias feature from real world,then integrated them into the factorization machine,which provided the high-order interactions between the different biased users and items.The experimental results on MovieLens datasets demonstrate that the proposed algorithm has lower prediction error than other traditional matrix factorization algorithms,which shows its better recommender performance.关键词
推荐系统/矩阵因子分解/因子分解机/评分偏差Key words
recommender system/matrix factorization/factorization machine/rating bias分类
信息技术与安全科学引用本文复制引用
王子豪,徐桂琼..基于高阶偏差的因子分解机推荐算法[J].计算机应用研究,2017,34(2):339-342,4.基金项目
国家自然科学基金资助项目(11201290,61104042) （11201290,61104042）
