Fuzzy Decision Support for Service Selection in E-Business Environments

Schmidt, S; Chang, E; Dillon, TS; Steele, RJ

Fuzzy Decision Support for Service Selection in E-Business Environments

Schmidt, S Chang, E Dillon, TS Steele, RJ

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Publisher:: IEEE
Publication Type:: Conference Proceeding
Citation:: Computational Intelligence in Multicriteria Decision Making, IEEE Symposium on, 2007, pp. 374 - 381
Issue Date:: 2007-01

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Field	Value	Language
dc.contributor.author	Schmidt, S	en_US
dc.contributor.author	Chang, E	en_US
dc.contributor.author	Dillon, TS	en_US
dc.contributor.author	Steele, RJ	en_US
dc.contributor.editor	Bonissone, P	en_US
dc.date	2007-04-01	en_US
dc.date.issued	2007-01	en_US
dc.identifier.citation	Computational Intelligence in Multicriteria Decision Making, IEEE Symposium on, 2007, pp. 374 - 381	en_US
dc.identifier.isbn	1-4244-0702-8	en_US
dc.identifier.uri	http://hdl.handle.net/10453/2363
dc.description.abstract	The emergence of semantic overlay networks as instruments to improve security, trust and stability in distributed virtual communities is recognized widely in the research community. We propose a fuzzy logic based framework which integrates social information such as trustworthiness, reputation and credibility ratings for individuals, alliances, organizations, services and products in e-commerce markets. This framework is designed to support the decision making process of autonomous agents during the selection of the optimal business partner. Fuzzy systems provide the ideal capabilities to process multiple criteria, which are composed of imprecise information and attribute definitions expressed in natural language. The proposed fuzzy models implement the DEco Arch framework and ontologies which provide details about concepts and their relationships in virtual communities	en_US
dc.publisher	IEEE	en_US
dc.relation.ispartof	Computational Intelligence in Multicriteria Decision Making, IEEE Symposium on	en_US
dc.relation.ispartof	IEEE Symposium on Computational Intelligence in Multicriteria Decision Making	en_US
dc.relation.isbasedon	10.1109/MCDM.2007.369116	en_US
dc.rights	© 2007 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.	en_US
dc.title	Fuzzy Decision Support for Service Selection in E-Business Environments	en_US
dc.type	Conference Proceeding
utslib.location	USA	en_US
utslib.location.activity	Honolulu, USA	en_US
utslib.for	0801 Artificial Intelligence and Image Processing	en_US
dc.location.activity	Honolulu, USA	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Electrical and Data Engineering
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Software
utslib.copyright.status	closed_access
pubs.consider-herdc	true	en_US
pubs.place-of-publication	USA	en_US
pubs.start-date	2007-04-01	en_US

Abstract:

The emergence of semantic overlay networks as instruments to improve security, trust and stability in distributed virtual communities is recognized widely in the research community. We propose a fuzzy logic based framework which integrates social information such as trustworthiness, reputation and credibility ratings for individuals, alliances, organizations, services and products in e-commerce markets. This framework is designed to support the decision making process of autonomous agents during the selection of the optimal business partner. Fuzzy systems provide the ideal capabilities to process multiple criteria, which are composed of imprecise information and attribute definitions expressed in natural language. The proposed fuzzy models implement the DEco Arch framework and ontologies which provide details about concepts and their relationships in virtual communities

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http://hdl.handle.net/10453/2363