计算机与数字工程2017，Vol.45Issue(4)：613-615,628,4.DOI:10.3969/j.issn.1672-9722.2017.04.003
基于用户的优化协同过滤推荐算法
Collaborative Filtering Recommendation Optimization Based on User
摘要
Abstract
In order to improve accuracy of the traditional collaborative filtering algorithm select user neighbor set, this paper proposes an improved collaborative filtering recommendation algorithm.The algorithm selects the user common rating data to calculate the user's similarity, also considers the consistency of the score data, constructes evaluation matrix, and alleviates the similarity calculation value and actual value deviation by user rating consistent times thanratingitem number as a penalty function is introduced into the similarity calculation.Experimental results show that the improved algorithm proposed in this paper significantly increases the prediction accuracy, so as to improve the quality of recommendation.关键词
邻居集/协同过滤/一致矩阵/相似度Key words
neighbor set/collaborative filtering/consistent matrix/similarity分类
信息技术与安全科学引用本文复制引用
卫泽,周登文..基于用户的优化协同过滤推荐算法[J].计算机与数字工程,2017,45(4):613-615,628,4.基金项目
国家自然科学基金项目(编号:61372184) （编号:61372184）
北京市自然科学基金项目(编号:4162056)资助. （编号:4162056）
