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Title: Utilizing Linked Open Data for Web Service Selection and Composition to Support e-Commerce Transactions
Authors: Vesyropoulos, Nikolaos
Georgiadis, Christos K.
Pimenidis, Elias
Type: Conference Paper
Subjects: FRASCATI::Natural sciences::Computer and information sciences
Keywords: Web services
quality of service
Issue Date: 2016
Publisher: Springer Verlag
Volume: 9875
Issue: 8th International Conference on Computational Collective Intelligence, ICCCI 2016
First Page: 533
Last Page: 541
Volume Title: Computational Collective Intelligence
Part of Series: Lecture Notes in Computer Science
Part of Series: Lecture Notes in Computer Science
Abstract: Web Services (WS) have emerged during the past decades as a means for loosely coupled distributed systems to interact and communicate. Nevertheless, the abundance of services that can be retrieved online, often providing similar functionalities, can raise questions regarding the selection of the optimal service to be included in a value added composition. We propose a framework for the selection and composition of WS utilizing Linked open Data (LoD). The proposed method is based on RDF triples describing the functional and non-functional characteristics of WS. We aim at the optimal composition of services as a result of specific SPARQL queries and personalized weights for QoS criteria. Finally we utilize an approach based on the particle swarm optimization (PSO) method for the ranking of returned services.
ISBN: 978-3-319-45242-5
ISSN: 0302-9743
Other Identifiers: 10.1007/978-3-319-45243-2_49
Appears in Collections:Department of Applied Informatics

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