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The PORSCE II framework: using AI planning for automated Semantic Web service composition

Published online by Cambridge University Press:  18 February 2013

Ourania Hatzi ,
Dimitris Vrakas ,
Nick Bassiliades ,
Dimosthenis Anagnostopoulos  and
Ioannis Vlahavas
Ourania Hatzi
Affiliation:
Department of Informatics and Telematics, Harokopio University of Athens, Harokopou 89, 17671 Athens, Greece; e-mail: [email protected], [email protected]
Dimitris Vrakas
Affiliation:
Department of Informatics, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece; e-mail: [email protected], [email protected], [email protected]
Nick Bassiliades
Affiliation:
Department of Informatics, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece; e-mail: [email protected], [email protected], [email protected]
Dimosthenis Anagnostopoulos
Affiliation:
Department of Informatics and Telematics, Harokopio University of Athens, Harokopou 89, 17671 Athens, Greece; e-mail: [email protected], [email protected]
Ioannis Vlahavas
Affiliation:
Department of Informatics, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece; e-mail: [email protected], [email protected], [email protected]
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Abstract

This paper presents PORSCE II, an integrated system that performs automatic Semantic Web service composition exploiting artificial intelligence (AI) techniques, specifically planning. Essential steps in achieving Web service composition include the translation of the Web service composition problem into a solver-ready planning domain and problem, followed by the acquisition of solutions, and the translation of the solutions back to Web service terms. The solutions to the problem, that is, the descriptions of the desired composite service, are obtained by means of external domain-independent planning systems, they are visualized and finally evaluated. Throughout the entire process, the system exploits semantic information extracted from the semantic descriptions of the available Web services and the corresponding ontologies, in order to perform composition under semantic awareness and relaxation.

Type
Articles
Information
The Knowledge Engineering Review , Volume 28 , Special Issue 2: Knowledge Engineering for Planning and Scheduling , June 2013 , pp. 137 - 156
Copyright
Copyright © Cambridge University Press 2013 

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