%A WANG Shao-wei, LIU Jian-xun, CAO Bu-qing, TANG Ming-dong and WANG Xian %T Recommended Method of Mashup Services Based on Information Entropy Multi-attribute Decision-making %0 Journal Article %D 2015 %J Computer Science %R 10.11896/j.issn.1002-137X.2015.02.055 %P 263-266 %V 42 %N 2 %U {https://www.jsjkx.com/CN/abstract/article_3161.shtml} %8 2018-11-14 %X 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.