Semantic Web Service Discovery Framework using Multi-Agents System And NLP Techniques
As a consequently increase amount of web services available on the web, automatic discovery presents a great challenge, in order to satisfy this requirement, semantic discovery approaches based on ontologies have been developed. However, end-users do not have knowledge about semantic web languages to express their requirements.
In this paper, we propose an automatic discovery framework based on multi-agent systems and natural language processing techniques to match a user request. The framework allows semantic matching through a set of semantic web services in order to enhance the accuracy of the discovery pattern, and to find a relevant match to the user request composed of keywords written in natural language. The use of multi-agent systems provide us the possibility to decrease the run-time by parallelizing simultaneous tasks, also, to implement various natural language processing techniques and matchmaking algorithms, and finally, they allow us to measure the users satisfaction through their behaviors dashboard analyze.
(1) A. Bener, V. Ozadali, and E. Ilhan, Semantic matchmaker with precondition and effect matching using SWRL. Expert Systems with Applications, 36(5), 9371–9377, (2009).
(2) A. Navarro, A. da Silva, A Metamodel-based definition of a conversion mechanism between SOAP and RESTful web services, Computer Standards & Interfaces, Volume 48, Pages 49-70, ISSN 0920-5489? November 2016.
(3) Bird, Steven, Edward Loper and Ewan Klein (2009), Natural Language Processing with Python. O’Reilly Media Inc. (2009)
(4) Brill, E., 1992. A simple rule-based part of speech tagger. In: Proceedings of the Workshop on Speech and Natural Language. Association for Computational Linguistics, pp. 112–116.
(5) C. Castelfranchi, Y. Lespérance, Developing Multi-agent Systems with JADE Intelligent Agents, In Intelligent Agents VII Agent Theories Architectures and Languages, Vol. 1986,(2001)
(6) D. D. Lewis,Y. Yang, T. Rose, and Li, F. RCV1: A New Benchmark Collection for Text Categorization Research. Journal of Machine Learning Research, 5:361-397, 2004. http://www.jmlr.org/papers/volume5/lewis04a/lewis04a.pdf.
(7) D. Martin, M. Paolucci, S. McIlraith,M. Burstein,D. McDermott, D. McGuinness and al. Bringing semantics to web services: The OWL-S approach. Semantic Web Services and Web Process Composition; p 26-42, 2005.
(8) EU IST, FIT-IT. (2008). WSMO4J API. Available from<http://wsmo4j.sourceforge.net/>.
(9) H. C. Boas, “Bilingual FrameNet Dictionaries for Machine Translation”, in Proceedings of the Third International Conference on Language Resources and Evaluation, Las Palmas, vol. IV, pp. 1364-1371. 2002.
(10) H. Cancela, A. Cuadros-Vargas, A. D. Renzis, M. Garriga, A. Flores, A. Cechich, A. Zunino, CLEI 2015, the XLI Latin American Computing ConferenceCase-based Reasoning for Web Service Discovery and Selection, Electronic Notes in Theoretical Computer Science, Volume 321, Pages 89-112, 2016.
(11) Hai H. Wang, Nick Gibbins, Terry R. Payne, Domenico Redavid, A formal model of the Semantic Web Service Ontology (WSMO), Information Systems, Volume 37, Issue 1, Pages 33-60, March 2012.
(12) HP Labs Semantic Web, (2009). Jena. Available from<http://jena.sourceforge.net/>.
(13) J.M. García, D. Ruiz, A. Ruiz-CortésImproving semantic web services discovery using Sparql-based repository filteringWeb Semantics: Science, Services and Agents on the World Wide Web, 17, pp. 12–24 (2012).
(14) M. B. Juric, A. Sasa, B. Brumen, I. Rozman, WSDL and UDDI extensions for version support in web services, Journal of Systems and Software, Volume 82, Issue 8, Pages 1326-1343, August 2009.
(15) M. El Kholy and A. Elfatatry, "Intelligent broker a knowledge based approach for semantic web services discovery," Evaluation of Novel Approaches to Software Engineering (ENASE), 2015 International Conference on, Barcelona, pp. 39-44, 2015.
(16) M. Paolucci, T. Kawamura, T.R. Payne, K. Sycara, Semantic matching of web services capabilitiesThe Semantic Web–ISWC 2002, pp. 333–347, Springer (2002)
(17) OASIS, 2004. UDDI Version 3.0.2, UDDI Spec Technical Committee.
(18) openRDF.org. (2009). Sesame. Available from<http://www.openrdf.org/>.
(19) P. Li, M. Comerio, A. Maurino and F. D. Paoli, "Advanced Non-functional Property Evaluation of Web Services," Web Services, 2009. ECOWS '09. Seventh IEEE European Conference on, Eindhoven, 2009.
(20) Porter, Martin F. An algorithm for suffix stripping. Program 14 (3): 130-137.1980.
(21) R. J. Rabelo, O. Noran and P. Bernus, "Towards the Next Generation Service Oriented Enterprise Architecture," 2015 IEEE 19th International Enterprise Distributed Object Computing Workshop, Adelaide, SA, 2015, pp. 91-100.
(22) R. Navigli, & P. Velardi. Structural semantic interconnections: A knowledgebased approach to word sense disambiguation.IEEE transactions on pattern analysis and machine intelligence (Vol. 27, pp. 1075–1086). IEEE Computer Society (2005).
(23) Venkat N. Gudivada, Dhana Rao, Vijay V. Raghavan, Chapter 9 - Big Data Driven Natural Language Processing Research and Applications, In: Venu Govindaraju, Vijay V. Raghavan and C.R. Rao, Editor(s), Handbook of Statistics, Elsevier, Volume 33, Pages 203-238, 2015.
(24) W3C, 2007. Web Services Description Language (WSDL) Version 2.0, W3C Recommendation.