计算机工程与应用Issue(5)：137-141,5.DOI:10.3778/j.issn.1002-8331.1405-0236
基于改进最近邻的协同过滤推荐算法
Collaborative filtering algorithm based on improved nearest neighbors
摘要
Abstract
Aiming to the problems that the quality and precision are caused by the sparse user scorings and cold-start, a novel collaborative filtering algorithm based on improved nearest neighbors is proposed in this paper. User-item matrix is established, and similarity between items and users is measured, the nearest neighbor of items and users is acquired, in which the particle swarm optimization algorithm is used to select the optimal value of the parameter k, the simulation experi-ments are carried out on MovieLens and Book-Crossing dataset. The results show that the proposed algorithm can achieve lower MAE and efficiently improve recommendation precision, and it can enhance the quality of recommendations.关键词
协同过滤/改进最近邻/粒子群优化算法/参数选择Key words
collaborative filtering/improved nearest neighbor/particle swarm optimization algorithm/selecting parameters分类
信息技术与安全科学引用本文复制引用
硕良勋,柴变芳,张新东..基于改进最近邻的协同过滤推荐算法[J].计算机工程与应用,2015,(5):137-141,5.基金项目
国家自然科学基金（No.61370129）；河北省科技计划项目（No.13210702D）。 （）
