电子科技大学学报2018，Vol.47Issue(1)：112-116,152,6.DOI:10.3969/j.issn.1001-0548.2018.01.017
一种引入加权异构信息的改进协同过滤推荐算法
An Improved Collaborative Filtering Recommendation Algorithm with Weighted Heterogeneous Information
摘要
Abstract
Collaborative filtering is oneofthe most successful recommendation technologies, and the quality of collaborative filtering is determinedby the accuracy of the nearest neighbors. Data sparsity problem and similarity metricsseriously affect the choice of the nearest neighbors. Different from traditional recommendation tasks, in this paper, we propose an improved meta path-based collaborative filtering algorithm for weighted heterogeneous information networks. Firstly, we calculate the similarity among users based on different meta path by utilizing the rich semantic information and attribute information in weighted heterogeneous networks. Then we apply the similarity to user-based collaborative filtering algorithm and get multiple predicted rating scores based on different similarity. Finally we calculate the final predicted scores by combining various meta path information using supervised machine learning algorithms. The method is evaluated with the extended MovieLens dataset and experimental results show that our approach outperforms several traditional algorithms and make the result of recommendation more accurate in terms of accuracy.关键词
协同过滤/元路径/推荐系统/相似度/加权异构信息Key words
collaborative filtering/meta path/recommendation system/similarity/weighted heterogeneous information分类
信息技术与安全科学引用本文复制引用
张海霞,吕振,张传亭,袁东风..一种引入加权异构信息的改进协同过滤推荐算法[J].电子科技大学学报,2018,47(1):112-116,152,6.基金项目
山东省自主创新及成果转化重大专项(2013ZHZX2C0102, 2014ZZCX03401) （2013ZHZX2C0102, 2014ZZCX03401）
