title: Decision support for personalized cloud service selection through multi-attribute trustworthiness evaluation.
abstract: Facing a customer market with rising demands for cloud service dependability and security, trustworthiness evaluation techniques are becoming essential to cloud service selection. But these methods are out of the reach to most customers as they require considerable expertise. Additionally, since the cloud service evaluation is often a costly and time-consuming process, it is not practical to measure trustworthy attributes of all candidates for each customer. Many existing models cannot easily deal with cloud services which have very few historical records. In this paper, we propose a novel service selection approach in which the missing value prediction and the multi-attribute trustworthiness evaluation are commonly taken into account. By simply collecting limited historical records, the current approach is able to support the personalized trustworthy service selection. The experimental results also show that our approach performs much better than other competing ones with respect to the customer preference and expectation in trustworthiness assessment.
authors: School of Management, Hefei University of Technology, Hefei, P.R. China; Key Laboratory of Process Optimization and Intelligent Decision-Making, Ministry of Education, Hefei, P.R. China.
authors: Shuai
authors: S
authors: Ding
authors: Cheng-Yi
authors: CY
authors: Xia
authors: Tianjin Key Laboratory of Intelligence Computing and Novel Software Technology and Key Laboratory of Computer Vision and System (Ministry of Education), Tianjin University of Technology, Tianjin, P.R. China.
authors: Chen-Yi
authors: CY
authors: Xia
authors: School of Management, Hefei University of Technology, Hefei, P.R. China; Key Laboratory of Process Optimization and Intelligent Decision-Making, Ministry of Education, Hefei, P.R. China.
authors: Kai-Le
authors: KL
authors: Zhou
authors: School of Management, Hefei University of Technology, Hefei, P.R. China; Key Laboratory of Process Optimization and Intelligent Decision-Making, Ministry of Education, Hefei, P.R. China.
authors: Shan-Lin
authors: SL
authors: Yang
authors: The Joseph M. Katz Graduate School of Business, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America.
authors: Jennifer S
authors: JS
authors: Shang
mesh_terms: D002755:Choice Behavior; D016494:Computer Security; D003258:Consumer Behavior; D016247:Information Storage and Retrieval / Q000379:methods*; D015233:Models, Statistical