Ahmed Abid
ABSTRACT
Computing similarities between Web services is a main concern in Service Oriented Architecture as it allows to decide which services are likely to be matched into a composite workflow, or in other cases, which services can be substituted in order to ensure continuous service availability. With the high maturity achieved by the standards, tools and frameworks in the Semantic Web domain, measuring Web services similarities relies more than ever on semantic descriptions of services as well as on semantic relationships these descriptions may hold. In this paper we present a Framework for Web services composition based on computing semantic similarity between Web services. We particularly focus on Services Matching engine which uses the considered similarity measure first to classify Web services into classes of functionally similar Web services and then to propose a composite sequence of services that matches a requested goal. In both tasks, the presented framework appeals for best known techniques of similarity computing and data and knowledge extraction, respectively.
- A. Abid, N. Messai, M. Rouached, T. Devogele, and M. Abid. A semantic similarity measure for conceptual web services classification. In WETICE, IEEE 24th International Conference on, pages 128--133. IEEE, 2015. Google Scholar
Digital Library
- A. L. Blum and M. L. Furst. Fast planning through planning graph analysis. Artificial intelligence, 90(1):281--300, 1997. Google ScholarDigital Library
- E. G. Da Silva, L. F. Pires, and M. Van Sinderen. Towards runtime discovery, selection and composition of semantic services. Computer communications, 34(2):159--168, 2011. Google ScholarDigital Library
- X. Dong, A. Halevy, J. Madhavan, E. Nemes, and J. Zhang. Similarity search for web services. In the Thirtieth international conference on Very large data bases-Volume 30, pages 372--383, 2004. Google ScholarDigital Library
- K. Elgazzar, A. E. Hassan, and P. Martin. Clustering WSDL documents to bootstrap the discovery of web services. In Web Services (ICWS), 2010 IEEE International Conference on, pages 147--154. IEEE, 2010. Google ScholarDigital Library
- B. Ganter and R. Wille. Formal concept analysis: mathematical foundations. Springer Science & Business Media, 2012.Google ScholarDigital Library
- O. Hatzi, M. Nikolaidou, D. Vrakas, N. Bassiliades, D. Anagnostopoulos, and I. Vlahavas. Semantically aware web service composition through AI planning. IJAIT, 2015.Google ScholarCross Ref
- F. Lécué and A. Léger. A formal model for semantic web service composition. In The Semantic Web-ISWC 2006, pages 385--398. Springer, 2006. Google ScholarDigital Library
- F. Lécué, E. Silva, and L. F. Pires. A framework for dynamic web services composition. In Emerging Web Services Technology. Springer, 2008. Google ScholarCross Ref
- F. Liu, Y. Shi, J. Yu, T. Wang, and J. Wu. Measuring similarity of web services based on WSDL. In IEEE International Conference on Web Services (ICWS), 2010. Google ScholarDigital Library
- M. Paolucci, T. Kawamura, T. R. Payne, and K. Sycara. Semantic matching of web services capabilities. In The Semantic Web ISWC 2002. Springer. Google ScholarDigital Library
- P. Plebani and B. Pernici. URBE: Web service retrieval based on similarity evaluation. Knowledge and Data Engineering, IEEE Transactions on, 2009. Google ScholarDigital Library
- P. Rodriguez Mier, C. Pedrinaci, M. Lama, and M. Mucientes. An integrated semantic web service discovery and composition framework. IEEE Transactions on Services Computing, 2015.Google Scholar
- D. Sánchez, M. Batet, D. Isern, and A. Valls. Ontology-based semantic similarity: A new feature-based approach. Expert Systems with Applications, 2012. Google ScholarDigital Library
- D. E. Wilkins. Practical planning. Elsevier Science, 2014.Google Scholar
- Y. Yan, B. Xu, and Z. Gu. Automatic service composition using and/or graph. In 2008 10th IEEE Conference E-Commerce Technology, pages 335--338, 2008. Google ScholarDigital Library
Index Terms
- Semantic similarity based web services composition framework
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