Dynamic Selection of Web Services with Recommendation System

Abstract

The realization of the semantic Web is underway with the development of an arena of services providing similar properties, capabilities, interfaces, and effects. To pick one of such similar services that matches the user's requirements is a difficult task and necessitates the use of an intelligent decision making framework. This paper addresses precisely this component. We present the design of a dynamic Web service selection framework that makes use of a semantic matcher to support matching and composition of software services. The framework also uses a recommendation system which helps a user to select the best service that matches his requirements. This recommendation system results in evolution of the framework to dynamically adapt to users requirements.