Please use this identifier to cite or link to this item:
https://ruomo.lib.uom.gr/handle/7000/662
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. |
URI: | https://doi.org/10.1007/978-3-319-45243-2_49 https://ruomo.lib.uom.gr/handle/7000/662 |
ISBN: | 978-3-319-45242-5 978-3-319-45243-2 |
ISSN: | 0302-9743 1611-3349 |
Other Identifiers: | 10.1007/978-3-319-45243-2_49 |
Appears in Collections: | Department of Applied Informatics |
Files in This Item:
File | Description | Size | Format | |
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Georgiadis_Utilizing_2016.pdf | 614,02 kB | Adobe PDF | View/Open |
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