A fuzzy model for reasoning about reputation in web services

Reputation systems are typically based on ratings given by the users. When there are no mechanisms in place to de-tect collusion and deception, combining user testimonies as such to form a provider’s reputation may not give an ac-curate assessment, especially if the context of the ratings is not known. Moreover, such systems are vulnerable to manipulations by malicious users. Hence it becomes essen-tial to establish the validity of the ratings prior to using them in formulating reputation based on such ratings. It is important to identify the rationale behind the ratings so that similar ratings (or ratings pertaining to a context) can be aggregated to obtain a reputation value meaningful in that context. We propose a fuzzy approach to analyze user rating behavior to infer the rationale for ratings in a web services environment. This inference of rationale facilitates the system to validate ratings, detect deception and collu-sion, identify user preferences and provide recommendations to users