计算机应用研究2017，Vol.34Issue(10)：2905-2908,4.DOI:10.3969/j.issn.1001-3695.2017.10.006
基于谱聚类与多因子融合的协同过滤推荐算法
Collaborative filtering recommendation algorithm based on spectral clustering and fusion of multiple factors
摘要
Abstract
Due to the problems of traditional collaborative filtering recommendation algorithm,included the data sparsity,ignored the users' time context information and preference for interest items,this paper proposed a collaborative filtering recommendation algorithm based on spectral clustering and multiple factors.Firstly,it integrated FCM into the key step of the spectral clustering,and determined the cluster number via cluster validity index,which could reduce the cost to generate a set of the nearest neighbors.Then,it improved the similarity measure by combing the Salton factor,time decay factor and user pre-ference factor.Finally,it generated the recommendation list for the objective user combining the system's current time.The experimental results on MovieLens show that the proposed algorithm improves recommendation quality in accuracy,cove-rage and novelty.关键词
协同过滤/谱聚类/Salton因子/时间衰减因子/用户偏好因子Key words
collaborative filtering/spectral clustering/Salton factor/time decay factor/user preference factor分类
信息技术与安全科学引用本文复制引用
李倩,李诗瑾,徐桂琼..基于谱聚类与多因子融合的协同过滤推荐算法[J].计算机应用研究,2017,34(10):2905-2908,4.基金项目
国家自然科学基金资助项目(11201290) （11201290）
