沈阳工业大学学报2018，Vol.40Issue(3)：316-321,6.DOI:10.7688/j.issn.1000-1646.2018.03.14
基于用户聚类的二分图网络协同推荐算法
Collaborative recommendation algorithm for bipartite networks based on user clustering
摘要
Abstract
Aiming at the problems about data sparsity and limited scalability in the application of collaborative filtering recommendation system, a collaborative recommendation algorithm for bipartite networks based on user clustering was proposed. The user center clustering was carried out for the bipartite networks in the user clustering stage, and the user clustering centers and the corresponding groups were obtained. In addition,more recommendation data were provided for the target users based on the evaluation information of user group. In the collaborative recommendation stage, the prediction scoring was finished for the projects without scoring around the clustering centers and their groups, and the Top-n projects with the highest comprehensive scores were recommended for the users. The results show that the proposed algorithm can enhance the recommendation accuracy of target users,and improve the diversity of collaborative recommendation.关键词
协同推荐/内容推荐/二分图网络/聚类/推荐系统/数据稀疏性/准确性/多样性Key words
collaborative recommendation/content-based recommendation/bipartite network/clustering/recommendation system/data sparsity/accuracy/diversity分类
信息技术与安全科学引用本文复制引用
郑怀宇..基于用户聚类的二分图网络协同推荐算法[J].沈阳工业大学学报,2018,40(3):316-321,6.基金项目
福建省科技厅科技平台建设项目(2015Y2001-58). （2015Y2001-58）
