计算机科学与探索Issue(5)：565-574,10.DOI:10.3778/j.issn.1673-9418.1412034
基于混合协同过滤的个性化Web服务推荐
Personalized Web Services Recommendation Based on Hybrid Collaborative Fil-tering Algorithm
摘要
Abstract
With the number increasing of Web services, recommending and selecting the personalized Web services for consumers has become one of the most important challenges in the field of service computing. This paper studies the approach for personalized Web services recommendation and proposes a model-based and memory-based quality of service (QoS) prediction approach for Web services. In the proposed approach, the consumers’expectation, rating and the QoS information are quantified. And based on the objective QoS data and the subjective rating, the quality of services is predicted by clustering, mapping and aggregation. The result is a list of recommended services for selec-tion. In addition, this paper designs a prediction framework, and realizes the information collecting and processing and personalized Web services recommendation through the framework. The experimental results demonstrate that compared with most other service recommendation approaches, the proposed approach increases the accuracy of rec-ommendation results.关键词
Web服务/聚类/服务质量预测/个性化/推荐Key words
Web service/clustering/QoS prediction/personalization/recommendation分类
信息技术与安全科学引用本文复制引用
张雪洁,王志坚,张伟建..基于混合协同过滤的个性化Web服务推荐[J].计算机科学与探索,2015,(5):565-574,10.基金项目
The National Key Technology Research and Development Program of China under Grant Nos.2013BAB05B01,2013BAB06B04(国家科技支撑计划项目) （国家科技支撑计划项目）
the Fundamental Research Funds for the Central Universities of China under Grant No.2013B16114(中央高校基本科研业务费专项资金) （中央高校基本科研业务费专项资金）
the Open Foundation of Huai’an Research Institute of Hohai University under Grant No.2014502512 （）
