Computer Science ›› 2015, Vol. 42 ›› Issue (2): 263-266.doi: 10.11896/j.issn.1002-137X.2015.02.055

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

WANG Shao-wei, LIU Jian-xun, CAO Bu-qing, TANG Ming-dong and WANG Xian   

  • Online:2018-11-14 Published:2018-11-14

Abstract: 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 Top-K 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.

Key words: Information entropy,Multi-attribute decision-making,Mashup service recommendation

[1] Wikipedia.http://en.wikipedia.org/wiki/Mashup
[2] Weilong D,Guiling W,Yanbo H,et al.A Pattern-Oriented Impact Analysis Approach for Mashups[C]∥Proceedings of the 2010 Fifth IEEE International Symposium on Service Oriented System Engineering.2010:55-58
[3] Lathem J,Gomadam K,Sheth A P.Sa-rest and (s) mashups:Adding semantics to restful services[C]∥ICSC 2007.Irvine,California,USA,2007:469-476
[4] Elmeleegy H,Ivan A,Akkiraju R,et al.Mashup advisor:A re-commendation tool for mashup development[C]∥ICWS2008.2008:337-344
[5] Programmable Web.http://www.programmableweb.com/
[6] Menascé D A.QoS Issues in Web Services[J].IEEE Internet Computing,2002,6(6):72-74
[7] Raza M.A Methodology for Quality-based Mashup of DataSources[C]∥IIWAS 2008.2008
[8] Picozzi M.Quality-based recommendations for Mashup composition[C]∥ICWE 2010.2010:360-371
[9] Cao J.Data Source Recommendation for Building Mashup Applications[C]∥WISA2010.2010:220-224
[10] 胡旭东,曾国荪,陈波.一种基于非功能属性决策的可信Web服务发现模型[J].计算机科学,2009,36(2):95-98
[11] W Hei-jia,L Chang-xing,H Zong-xian.Combining subjectiveand objective QoS factors for personalized Web serivce selection[J].Expert Systems with Applicaions,2007,32(2):571-584 (下转第291页)(上接第266页)
[12] 陶春华,冯志勇.QoS感知的Web服务推荐模型[J].计算机应用研究,2010(10):3902-3905
[13] Jin X.A Web Recommendation System Based on Maximum Entropy[C]∥Information Technology Coding and Computing (ITCC’05).Las Vegas,Nevada,April 2005
[14] 康国胜,刘建勋,唐明董,等.基于主成分分析的Web服务选择算法[J].小微型计算机,2013
[15] Rosenfeld R.Adaptive statistical language modeling:A maximum entropy approach[D].Carnegie Mellon University,1994
[16] 赵华龙.基于信息熵多属性决策的投资评价研究[J].商场现代化,2008,545(20):156-157
[17] 曾三云,龙君.基于信息熵的模糊多属性决策方法[J].广西科学,2008,15(2):135-137
[18] 施聪莺,徐朝军,杨晓江.TFIDF算法研究综述[J].计算机应用,2009(S1):167-170
[19] Mashup.2014.http://125.221.225.2:8080/Mashup
[20] Jrvelin K,Keklinen J.Cumulated gain-based evaluation of IR techniques[J].ACM Transactions on Information Systems,2002,20(4):422-446

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