The Community for Technology Leaders
RSS Icon
Issue No.03 - July-September (2009 vol.2)
pp: 210-222
Aviv Segev , Korean Advanced Institute of Science and Technology, Daejon
Eran Toch , Carnegie-Mellon University, Pittsburgh
In this work, we propose a two-step, context-based semantic approach to the problem of matching and ranking Web services for possible service composition. We present an analysis of different methods for classifying Web services for possible composition and supply a context-based semantic matching method for ranking these possibilities. Semantic understanding of Web services may provide added value by identifying new possibilities for compositions of services. The semantic matching ranking approach is unique since it provides the Web service designer with an explicit numeric estimation of the extent to which a possible composition “makes sense.” First, we analyze two common methods for text processing, TF/IDF and context analysis; and two types of service description, free text and WSDL. Second, we present a method for evaluating the proximity of services for possible compositions. Each Web service WSDL context descriptor is evaluated according to its proximity to other services' free text context descriptors. The methods were tested on a large repository of real-world Web services. The experimental results indicate that context analysis is more useful than TF/IDF. Furthermore, the method evaluating the proximity of the WSDL description to the textual description of other services provides high recall and precision results.
Intelligent Web services and semantic Web, Internet reasoning services, Web text analysis.
Aviv Segev, Eran Toch, "Context-Based Matching and Ranking of Web Services for Composition", IEEE Transactions on Services Computing, vol.2, no. 3, pp. 210-222, July-September 2009, doi:10.1109/TSC.2009.14
[1] E. Christensen, F. Curbera, G. Meredith, and S. Weerawarana, “WSDL Web Services Description Language,” W3C Candidate Recommendation, , 2001.
[2] C. Platzer and S. Dustdar, “A Vector Space Search Engine for Web Services,” Proc. Third European Conf. Web Services (ECOWS '05), 2005.
[3] A. Ankolekar, D. Martin, Z. Zeng, J. Hobbs, K. Sycara, B. Burstein, M. Paolucci, O. Lassila, S. Mcilraith, S. Narayanan, and P. Payne, “DAML-S: Semantic Markup for Web Services,” Proc. Int'l Semantic Web Workshop (SWWS '01), July 2001.
[4] R. Akkiraju, J. Farrell, J. Miller, M. Nagarajan, M.T. Schmidt, A. Sheth, and K. Verma, “WSDL-S Web Service Semantics,” W3C Candidate Recommendation,, 2005.
[5] S. Bechhofer, F. van Harmelen, J. Hendler, I. Horrocks, D. McGuinness, P. Patel-Schneider, and L. Stein, “OWL Web Ontology Language Reference,” W3C, W3C Candidate Recommendation,, 2004.
[6] M. Paolucci, T. Kawamura, T. Payne, and K. Sycara, “Semantic Matching of Web Services Capabilities,” Proc. Int'l Semantic Web Conf., 2002.
[7] Introduction to Modern Information Retrieval, G. Salton and M.McGill, eds. McGraw-Hill, 1983.
[8] A. Segev, M. Leshno, and M. Zviran, “Context Recognition Using Internet as a Knowledge Base,” J. Intelligent Information Systems, vol. 29, no. 3, pp. 305-327, 2007.
[9] A. Segev and A. Gal, “Putting Things in Context: A Topological Approach to Mapping Contexts to Ontologies,” J. Data Semantics, vol. 9, pp. 113-140, 2007.
[10] A.K. Dey, “Providing Architectural Support for Building Context-Aware Applications,” PhD thesis, Georgia Inst. of Tech nology, 2000.
[11] J. Rao, D. Dimitrov, P. Hofmann, and N. Sadeh, “A Mixed Initiative Approach to Semantic Web Service Discovery and Composition: Sap's Guided Procedures Framework,” Proc. IEEE Int'l Conf. Web Services (ICWS '06), pp. 401-410, 2006.
[12] J. Farrell and H. Lausen, “Semantic Annotations for wsdl and xml Schema SAWSDL,” W3C Candidate Recommendation, /, 2007.
[13] A. Heß, E. Johnston, and N. Kushmerick, “ASSAM: A Tool for Semi-Automatically Annotating Semantic Web Services,” Proc. Int'l Semantic Web Conf., pp. 320-334, 2004.
[14] C.J.V. Rijsbergen, Information Retrieval, second ed. Butterworths, 1979.
[15] T. Mitchell, Machine Learning. McGraw Hill, 1997.
[16] S. Robertson, “Understanding Inverse Document Frequency: On Theoretical Arguments for IDF,” J. Documentation, vol. 60, no. 5, pp.503-520, 2004.
[17] C. Mooers, “Descriptors,” Encyclopedia of Library and Information Science, vol. 7, pp. 31-45, Marcel Dekker, 1972.
[18] J. McCarthy, “Notes on Formalizing Context,” Proc. 13th Int'l Joint Conf. Artificial Intelligence, 1993.
[19] R. Chau and C. Yeh, “A Multilingual Text Mining Approach to Web Cross-Lingual Text Retrieval,” Knowledge-Based Systems, vol. 17, pp. 219-227, 2001.
[20] A. Segev and A. Gal, “Multilingual Ontology-Based Knowledge Management,” Decision Support Systems, vol. 45, pp. 567-584, 2008.
[21] A. Segev and A. Gal, “Ontology Verification Using Contexts,” Proc. European Conf. Artificial Intelligence (ECAI)—Workshop Contexts and Ontologies: Theory, Practice and Applications, 2006.
[22] M. Klusch, B. Fries, M. Khalid, and K. Sycara, “OWLS-MX: Hybrid Semantic Web Service Retrieval,” Proc. First Int'l AAAI Fall Symp. Agents and the Semantic Web, 2005.
[23] S.C. Oh, “Effective Web-Service Composition in Diverse and Large-Scale Service Networks,” PhD dissertation, Univ. Park, 2006.
[24] G.A. Vouros, F. Dimitrokallis, and K. Kotis, “Look Ma, No Hands: Supporting the Semantic Discovery of Services without Ontologies,” Proc. Int'l Workshop Service Matchmaking and Resource Retrieval in the Semantic Web (SMRR), R.L. Hernandez, T.D. Noia, and I. Toma, eds., 2008.
[25] E. Toch, A. Gal, and D. Dori, “Automatically Grounding Semantically-Enriched Conceptual Models to Concrete Web Services,” ER, L. Delcambre, C. Kop, H. Mayr, J. Mylopoulos, and O. Pastor, eds., pp. 304-319, Springer, 2005.
[26] A. Patil, S. Oundhakar, A. Sheth, and K. Verma, “Meteor-s Web Service Annotation Framework,” Proc. 13th Int'l Conf. World Wide Web (WWW '04), pp. 553-562, 2004.
[27] Z. Duo, L. Juan-Zi, and X. Bin, “Web Service Annotation Using Ontology Mapping,” Proc. IEEE Int'l Workshop Service-Oriented System Eng. (SOSE '05), pp. 243-250, 2005.
[28] N. Oldham, C. Thomas, A.P. Sheth, and K. Verma, “Meteor-s Web Service Annotation Framework with Machine Learning Classification,” Proc. Int'l Workshop Semantic Web Services and Web Process Composition (SWSWPC '04), pp. 137-146, 2004.
[29] X. Dong, A. Halevy, J. Madhavan, E. Nemes, and J. Zhang, “Similarity Search for Web Services,” Proc. Int'l Conf. Very Large Data Bases, pp. 372-383, 2004.
[30] S. Bowers and B. Ludäscher, “Towards Automatic Generation of Semantic Types in Scientific Workflows,” Proc. Int'l Workshop Scalable Semantic Web Knowledge Base Systems (SSWS '05), pp. 207-216, 2005.
[31] K. Belhajjame, S.M. Embury, N.W. Paton, R. Stevens, and C.A. Goble, “Automatic Annotation of Web Services Based on Workflow Definitions,” ACM Trans. Web, vol. 2, no. 2, pp. 1-34, 2008.
[32] E. Sciore, M. Siegel, and A. Rosenthal, “Using Semantic Values to Facilitate Interoperability among Heterogeneous Information Systems,” ACM Trans. Database Systems, vol. 19, no. 2, pp. 254-290, 1994.
[33] M. Mrissa, C. Ghedira, D. Benslimane, Z. Maamar, F. Rosenberg, and S. Dustdar, “A Context-Based Mediation Approach to Compose Semantic Web Services,” ACM Trans. Internet Technology, vol. 8, no. 1, p. 4, 2007.
[34] A. Gal, A. Segev, and E. Toch, “Semantic Methods for Service Categorization—An Empirical Study,” Proc. Int'l Workshop Semantic Data and Service Integration (SDSI '07), 2007.
26 ms
(Ver 2.0)

Marketing Automation Platform Marketing Automation Tool