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Decision support for personalized cloud service selection through multi-attribute trustworthiness evaluation

Ding, S and Xia, CY and Zhou, KL and Yang, SL and Shang, JS (2014) Decision support for personalized cloud service selection through multi-attribute trustworthiness evaluation. PLoS ONE, 9 (6).

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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. © 2014 Ding et al.


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Details

Item Type: Article
Status: Published
Creators/Authors:
CreatorsEmailPitt UsernameORCID
Ding, S
Xia, CY
Zhou, KL
Yang, SL
Shang, JSSHANG@katz.pitt.eduSHANG
Contributors:
ContributionContributors NameEmailPitt UsernameORCID
EditorCsermely, PeterUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Date: 27 June 2014
Date Type: Publication
Journal or Publication Title: PLoS ONE
Volume: 9
Number: 6
DOI or Unique Handle: 10.1371/journal.pone.0097762
Schools and Programs: Joseph M. Katz Graduate School of Business > Business Administration
Refereed: Yes
Date Deposited: 16 Sep 2014 19:42
Last Modified: 02 Feb 2019 15:55
URI: http://d-scholarship.pitt.edu/id/eprint/23017

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