Towardsaframeworkfor Classification and Recommendation of Semantic Web Service Composition Approaches

Abstract

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.

Key Words:

• Semantic web services
• composition approaches
• classification
• taxonomy
• recommendation system
• ontology

Additional information

Notes on contributors

S. Kumar

Sandeep Kumar (B.Tech. (Hons. and Gold Medal), PG Course, Ph.D. Scholar) is with Department of Computer Engineering, Institute of Technology, BHU, Varanasi, India-221005. He is the member of review and editorial committees of many international publications. He has published around 15 papers in international journals and conferences and has authored two books. His current areas of interest include Semantic Web, Web-based systems, multi-agent systems, knowledge-based systems, and software engineering.

R.B. Mishra

R.B.Mishra (B.Sc, Eng.;M.Tech.; Ph.D.) is a reader with the Department of Computer Engineering, Institute of Technology, Banaras Hindu University (ITBHU), Varanasi, India-221005. He has around 30 years of experience in teaching and research. He has published more than 90 research papers and articles in journals and conferences. He has supervised three Ph.D. and 21 He has also visited as faculty to U.K. His current areas of interest include AI and its application to medicine, robotics and the Semantic Web.