Some service reputation approaches primarily consider the consumer's prior experience of the service via opinion feedback system, may neglect the effect of TrustTransition (TT) in the recommendations of others. The service reputation is propagated via referral network recommendations for service composition and eventually builds a distinct level of consumer trust in the service. Accordingly, the present study proposes a service selection model in which the reputation of a service provider is estimated by collecting consumer feedbacks and other's recommendations in open networks. The degree of service reputation is appropriately estimated using fuzzy Petri net (FPN) to model the referral activities across the social networks and outrank a set of service alternatives using the global reputation score of a service. Two examples of social services selection are used to demonstrate the proposed approach. The proposed model effectively solves the trust transition problem in the indirect recommendation of the service selection and also enables deception detection in terms of existing evidences for assessment of evaluator credibility that excludes the false evidences of dishonest evaluators.
|Number of pages||7|
|Journal||Computer Systems Science and Engineering|
|State||Published - Jul 2015|