A Framework for Semantic Web Services Discovery

Abstract

Web services in their current form do not express what a service actually does, i.e. they are limited in their ability to express the capabilities of a service. This limitation may be relaxed by providing a rich set of semantic annotations that augment the services description. Semantic descriptions of Web services are necessary in order to enable their automatic discovery, composition and execution across heterogeneous users and domains. In this thesis, we present a novel approach for the automatic discovery of Web services by categorizing the service using some semantic and statistical measures. A framework named `ADWebS' (Automatic Discovery of Web Services Semantically) has been proposed and designed for automatic discovery and categorization of Web services. Categorization process in ADWebS starts with incorporation of semantic description in the form of annotations by services publisher or developer, which are extracted from WSDL of annotated services. Semantic relatedness of each annotation or term is found with every candidate category using Normalized Google Distance (NGD). Next a non- parametric test Kruskal Wallis is applied and based on the median value achieved for each category, a service is permanently assigned to one or more pre-de_ned category(s). ADWebS provides a `Google-like' query interface to the service discoverer with a list of available candidate categories as a dropdown list. Performance of the ADWebS has been tested for service retrieval time, precision-at-n and scalability.