基于信息熵多属性决策的Mashup服务推荐方法  

Recommended Method of Mashup Services Based on Information Entropy Multi-attribute Decision-making

作　　者：王少伟[1] 刘建勋[1] 曹步清[1] 唐明董[1] 王弦[1] 

机构地区：[1]湖南科技大学计算机科学与工程学院知识处理与网络化制造湖南省普通高校重点实验室,湘潭411201

出　　处：《计算机科学》2015年第2期263-266,291,共5页Computer Science

基　　金：国家自然科学基金(61272063;61100054);教育部新世纪优秀人才支持计划项目(NCET-10-0140);湖南省杰出青年基金项目(11JJ1011);湖南省自然科学基金项目(12JJB009;12JJ6064);湖南省高校创新平台开放基金(09K085;12K105);湖南科技大学研究生创新基金(S120024)资助

摘　　要：随着Mashup服务的快速发展,如何在海量的服务集合中找到用户感兴趣的、服务质量高的Mashup服务,成为一个难题。针对该问题,提出一种基于信息熵多属性决策的Mashup服务推荐方法。首先建立用户兴趣模型和Mashup服务的质量(Quality of Service,QoS)模型;其次,利用信息熵多属性决策方法,预测用户对候选Mashup服务的综合评分,并将综合评分最高的Top-K Mashup服务推荐给用户;最后,在不同数据集上进行实验比较与分析,结果表明:基于信息熵多属性决策的Mashup服务推荐方法能够有效地为用户推荐其感兴趣的、高质量的Mashup服务。With the continuous development of Mashup services,how to find the services which have high quality and users are interested in becomes a hard work in a massive services.To solve this problem,this paper proposed a recommended method of Mashup services based on information entropy multi-attribute decision making.In this approach,firstly,user interest model and Mashup quality of service（QoS）model are created.Then,based on information entropy multi-attribute decision making method,the comprehensive score of the candidate Mashup services is predicted and TopK highest ones are recommended to the user.Finally,the large-scale experiments on Mashup service dataset show that the recommended method of Mashup services can effectively recommend a Mashup service list to user with high comprehensive quality,and has good scalability.

关 键 词：信息熵 多属性决策 Mashup服务推荐 

分 类 号：TP315[自动化与计算机技术—计算机软件与理论]