Towards a Framework for Classification and Recommendation of Semantic Web Service Composition Approaches
نویسنده
چکیده
Semantic web service (SWS) composition increases the capability of an application to satisfy user’s requests by theoretically generating an unlimited number of new services from the composition of limited service components. The performance of a SWS composition approach highly depends upon the situation of its use. In this paper, a framework called Technique Classification and Recommendation Framework has been proposed. It is composed of two systems: Taxonomical Classification System (TCS) and Technique Recommendation System (TRS). This framework presents a novel classification of various SWS composition approaches and provides recommendations to the user regarding the composition approach to use under given condition parameters. The framework can be of immense use for the selection of appropriate composition approach during the development of semantic web based systems.
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تاریخ انتشار 2010