IWSS: Intelligent Web Service selection for service-oriented applications

With growth in the number of Web Services (WS) offered over the Internet, discovery and selection of services has become achallenging job. The problem is particularly complex when there is large number of services providing the same or similar functionality. Mainstream approaches for WS selection rely on functional description of the service as published by the service provider. There is no provision for adapting the service selection behavior by taking into account users´ run-time experience with the service. The framework presented in this paper combines functional parameters of published WS with users´ Quality of Experience(QoE)in a Case Based Reasoning (CBR) system for precise selection of best WS corresponding to a user query. Experimental results show that the proposed approach gives much more precise results than naïve approaches.