Towards Explanation-Aware Selection in Internet-Scale Infrastructures: Generating Rationale for Web Services Ratings and Reputation

A collection of 1 billion publicly available web services can form an internet-scale infrastructure for building di-verse applications. For a given application, selection of ser-vices and service providers from this collection becomes im-portant and reputation is recognized as a key factor for this purpose. However, current reputation systems are limited in their ability to exchange reputation information between heterogeneous systems. To facilitate meaningful exchange and reuse of reputation information and for the overall de-termination of reputation, we identify the need to infer and explicate rationale for ratings. We present our knowledge based approach to inferring and explicating rationale for ratings. We show that this approach facilitates detection of deception and collusion, user preferences elicitation, expli-cation of rationale behind user ratings and generation of personalized service recommendations. 1