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Facilitating Web Service Taxonomy Generation : An Artificial Neural Network based Framework, A Prototype Systems, and Evaluation  

Hwang, You-Sub (College of Business Administration, University of Seoul)
Publication Information
Journal of Intelligence and Information Systems / v.16, no.2, 2010 , pp. 33-54 More about this Journal
Abstract
The World Wide Web is transitioning from being a mere collection of documents that contain useful information toward providing a collection of services that perform useful tasks. The emerging Web service technology has been envisioned as the next technological wave and is expected to play an important role in this recent transformation of the Web. By providing interoperable interface standards for application-to-application communication, Web services can be combined with component based software development to promote application interaction both within and across enterprises. To make Web services for service-oriented computing operational, it is important that Web service repositories not only be well-structured but also provide efficient tools for developers to find reusable Web service components that meet their needs. As the potential of Web services for service-oriented computing is being widely recognized, the demand for effective Web service discovery mechanisms is concomitantly growing. A number of public Web service repositories have been proposed, but the Web service taxonomy generation has not been satisfactorily addressed. Unfortunately, most existing Web service taxonomies are either too rudimentary to be useful or too hard to be maintained. In this paper, we propose a Web service taxonomy generation framework that combines an artificial neural network based clustering techniques with descriptive label generating and leverages the semantics of the XML-based service specification in WSDL documents. We believe that this is one of the first attempts at applying data mining techniques in the Web service discovery domain. We have developed a prototype system based on the proposed framework using an unsupervised artificial neural network and empirically evaluated the proposed approach and tool using real Web service descriptions drawn from operational Web service repositories. We report on some preliminary results demonstrating the efficacy of the proposed approach.
Keywords
웹서비스;분류체계;데이터 마이닝;인공신경망;프로토타입 시스템;군집화;평가;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
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1 Zhuge, H. and J. Liu, "Flexible Retrieval of Web Services", The Journal of Systems and Software, Vol.70(2004), 107-116.   DOI   ScienceOn
2 Lawrie, D., W. B. Croft, and A. Rosenberg, "Finding topic words for hierarchical summarization", in Proceedings of the 24th annual international ACM SIGIR conference on Research and Development information Retrieval, New Orleans, Louisiana, United States, 2001.
3 Lewis, D. D., "Evaluating Text Categorization", in Proceedings of the Speech and Natural Language Workshop. San Mateo, CA, 1991.
4 Honkela, T., S. Kaski, K. Lagus, and T. Kohonen, "WEBSOM-self-organizing maps of document collections", in Proceedings of WSOM'97, Workshop on Self-Organizing Maps, Espoo, Finland, 1997.
5 Dong, X., J. Madhava, and A. Halevy, "Similarity Search for Web Services", in Proceedings of VLDB Conference, Toronto, Canada, 2004.
6 Glover, E., D. M. Pennock, S. Lawrence, and R. Krovetz, "Inferring Hierarchical Descriptions", in Proceedings of the 11th International Conference on Information and Knowledge Management CIKM'02, McLean, VA, 2002.
7 Hatzivassiloglou, V. and K. R. McKeown, "Towards the Automatic Identification of Adjectival Scale：Clustering Adjectives According to Meaning", in Proceedings of the 31st ACL. Columbus, Ohio, USA, 1993.
8 Hwang, Y., "Evaluation of Web Service Similarity Assessment Methods", Journal of Intelligence and Information Systems, Vol.15, No.4(2009), 1-21.   과학기술학회마을
9 Kohonen, T., Self Organizing Maps, Third ed. Berlin：Springer, 2001.
10 Merkl, D. and A. Rauber, "Automatic labeling of self-organizing maps for information retrieval", in Proceedings of the 6th International Conference on Neural Information Processing ICONIP'99, Perth, WA, Australia,1999.
11 Muller, A., J. Dorre, P. Gerstl, and R. Seiffert, "The TaxGen Framework：Automating the Generation of a taxonomy for a large document collection", in Proceedings of the 32nd Hawaii International Conference on System Science(HICSS), Maui, Hawaii), 1999, 2034.
12 Popescul, A. and L. Ungar, "Automatic labeling of document clusters", Unpublished manuscript http://citeseer.nj.nec.com/popescul00automatic.html, 2000.
13 Sabou, M. and J. Pan, "Towards Improving Web Service Repositories through Semantic Web Techniques", Web Semantics：Science, Services and Agents on the World Wide Web, Vol.5, No.4(2007), 142-152.   DOI
14 Stroulia, E. and Y. Wang, "Structural and Semantic Matching for Assessing Web-Service Similarity", International Journal of Cooperative Information Systems, Vol.14, No.4(2005), 407-437.   DOI   ScienceOn
15 Swets, J. A., Effectiveness of Information Retrieval Methods, American Documents, 1969.
16 Yang, Y., "An Evaluation of Statistical Approaches to Text Categorization", Information Retrieval, 1), 1999, 69-90.   DOI   ScienceOn