Empirical Study for Semantic Annotation of Web Services
- DOI
- 10.2991/ijndc.2014.2.1.4How to use a DOI?
- Keywords
- Annotation, Web Service, SAWSDL, Semantic Web Services, Ontology Matching
- Abstract
Web services have become the main paradigm for the development of distributed software systems using a common set of technologies, including SOAP, WSDL and UDDI. This allows accessing to software components residing on different platforms and written in different programming languages. However, several tasks, including service discovery and composition, remain difficult to be automated. Thus, a new technology has emerged to solve this problem; it is the Semantic Web Services (SWS). One way to produce SWS is the annotation. In this paper, an approach to annotate Web services is presented. The approach consists of two main processes, categorization and matching. Both processes use ontology matching techniques. In particular, the two processes use similarity measures between entities, strategies to calculate similarities between sets and a threshold corresponding to the accuracy. Thus, an internal comparative study has been done to determine which strategy is appropriate to this approach, which measure gives best results and which threshold is optimum for the selected measure and strategy. An external comparative study has been also carried out to prove the efficacy of this approach compared to existing annotation approaches.
- Copyright
- © 2017, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - JOUR AU - Djelloul Bouchiha AU - Mimoun Malki AU - Djihad Djaa AU - Abdullah Alghamdi AU - Khalid Alnafjan PY - 2014 DA - 2014/01/01 TI - Empirical Study for Semantic Annotation of Web Services JO - International Journal of Networked and Distributed Computing SP - 35 EP - 44 VL - 2 IS - 1 SN - 2211-7946 UR - https://doi.org/10.2991/ijndc.2014.2.1.4 DO - 10.2991/ijndc.2014.2.1.4 ID - Bouchiha2014 ER -