WSCOLAB: STRUCTURED COLLABORATIVE TAGGING FOR WEB SERVICE MATCHMAKING

Maciej Gawinecki, Giacomo Cabri, Marcin Paprzycki, Maria Ganzha

2010

Abstract

One of the key requirements for the success of Service Oriented Architecture is discoverability of Web services. Unfortunately, application of authoritatively defined taxonomies cannot cope with the volume of services published on the Web. Collaborative tagging claims to address this problem, but is impeded by the lack of structure to describe Web service functions and interfaces. In this paper we introduce \structured collaborative tagging to improve Web service descriptions. Performance of the proposed technique obtained during the Cross-Evaluation track of the Semantic Service Selection 2009 contest is reported. Obtained results show that the proposed approach can be successfully used in both Web service tagging and querying.

References

  1. Al-Masri, E. and Mahmoud, Q. H. (2008a). Discovering Web Services in Search Engines. IEEE Internet Computing, 12(3).
  2. Al-Masri, E. and Mahmoud, Q. H. (2008b). Investigating Web Services on the World Wide Web. In WWW.
  3. Dietze, S., Benn, N., Conconi, J. D., and Cattaneo, F. (2009). Two-Fold Semantic Web Service Matchmaking-Applying Ontology Mapping for Service Discovery. In ASWC.
  4. Dong, X., Halevy, A. Y., Madhavan, J., Nemes, E., and Zhang, J. (2004). Similarity Search for Web Services. In VLDB.
  5. Fernández, A., Hayes, C., Loutas, N., Peristeras, V., Polleres, A., and Tarabanis, K. A. (2008). Closing the Service Discovery Gap by Collaborative Tagging and Clustering Techniques. In SMRR.
  6. Furnas, G. W., Fake, C., von Ahn, L., Schachter, J., Golder, S., Fox, K., Davis, M., Marlow, C., and Naaman, M. (2006). Why do tagging systems work? In CHI.
  7. Furnas, G. W., Landauer, T. K., Gomez, L. M., and Dumais, S. T. (1987). The vocabulary problem in humansystem communication. Commun. ACM, 30(11).
  8. Gawinecki, M. (2009a). Analysis of SeekDa Tags for Web Service Matchmaking. Technical report, University of Modena and Reggio-Emilia.
  9. Gawinecki, M. (2009b). http://mars.ing.unimo.it/wscolab/.
  10. Hagemann, S., Letz, C., and Vossen, G. (2007). Web Service Discovery - Reality Check 2.0. In NWESP, pages 113-118.
  11. Järvelin, K. and Kekäläinen, J. (2002). Cumulated gainbased evaluation of IR techniques. ACM Trans. Inf. Syst., 20(4):422-446.
  12. (2009). Java http://java.sun.com/javase/.
  13. Küster, U. (2010). JGDEval at S3 Contest 2009 - Results. http://fusion.cs.uni-jena.de/professur/jgdeval/jgdevalat-s3-contest-2009-results.
  14. Küster, U. and König-Ries, B. (2009). Relevance Judgments for Web Services Retrieval - A Methodology and Test Collection for SWS Discovery Evaluation. In ECOWS.
  15. Lausen, H. and Haselwanter, T. (2007). Finding Web Services. In ESTC.
  16. Merobase (2009). http://www.merobase.com/.
  17. Meyer, H. and Weske, M. (2006). Light-Weight Semantic Service Annotations through Tagging. In ICSOC, volume 4294 of LNCS, pages 465-470.
  18. Mika, P. (2005). Ontologies are us: A unified model of social networks and semantics. J. Web Sem., 5(1).
  19. Mili, H., Mili, F., and Mili, A. (1995). Reusing Software: Issues and Research Directions. IEEE Trans. Softw. Eng., 21(6):528-562.
  20. Montaner, M., L ópez, B., and De La Rosa, J. L. (2003). A Taxonomy of Recommender Agents on the Internet. Artif. Intell. Rev., 19(4):285-330.
  21. OCML (2009). http://kmi.open.ac.uk/projects/ocml/.
  22. OWL-S (2009). http://www.w3.org/Submission/2004/ SUBM-OWL-S-20041122/.
  23. Paolucci, M., Kawamura, T., Payne, T. R., and Sycara, K. P. (2002). Semantic Matching of Web Services Capabilities. In ISWC, pages 333-347.
  24. Prieto-Díaz, R. (1991). Implementing faceted classification for software reuse. Commun. ACM, 34(5):88-97.
  25. ProgrammableWeb (2009). http://programmableweb.com.
  26. S3 (2009). Semantic Service Selection contest. http://wwwags.dfki.uni-sb.de/ klusch/s3/html/2009.html.
  27. Salton, G. and Buckley, C. (1988). Term-weighting approaches in automatic text retrieval. Inf. Process. Manage., 24(5):513-523.
  28. SAWSDL (2009). http://www.w3.org/TR/sawsdl/.
  29. SeekDa (2009). http://seekda.com.
  30. Sen, S., Lam, S. K., Rashid, A. M., Cosley, D., Frankowski, D., Osterhouse, J., Harper, F. M., and Riedl, J. (2006). tagging, communities, vocabulary, evolution. In CSCW, pages 181-190.
  31. Shirky, C. (2005). Ontology is Overrated: Categories, Links, and Tags. http://www.shirky.com/ writings/ontology overrated.html.
  32. Xu, Z., Fu, Y., Mao, J., and Su, D. (2006). Towards the Semantic Web: Collaborative Tag Suggestions. In Proceedings of the Collaborative Web Tagging Workshop at the WWW 2006.
  33. Zaremski, A. M. and Wing, J. M. (1995). Signature Matching: A Tool for Using Software Libraries. ACM Trans. Softw. Eng. Methodol., 4(2):146-170.
  34. Zobel, J. and Moffat, A. (2006). Inverted files for text search engines. ACM Comput. Surv., 38(2):6.
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Paper Citation


in Harvard Style

Gawinecki M., Cabri G., Paprzycki M. and Ganzha M. (2010). WSCOLAB: STRUCTURED COLLABORATIVE TAGGING FOR WEB SERVICE MATCHMAKING . In Proceedings of the 6th International Conference on Web Information Systems and Technology - Volume 1: WEBIST, ISBN 978-989-674-025-2, pages 70-77. DOI: 10.5220/0002809200700077


in Bibtex Style

@conference{webist10,
author={Maciej Gawinecki and Giacomo Cabri and Marcin Paprzycki and Maria Ganzha},
title={WSCOLAB: STRUCTURED COLLABORATIVE TAGGING FOR WEB SERVICE MATCHMAKING},
booktitle={Proceedings of the 6th International Conference on Web Information Systems and Technology - Volume 1: WEBIST,},
year={2010},
pages={70-77},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002809200700077},
isbn={978-989-674-025-2},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 6th International Conference on Web Information Systems and Technology - Volume 1: WEBIST,
TI - WSCOLAB: STRUCTURED COLLABORATIVE TAGGING FOR WEB SERVICE MATCHMAKING
SN - 978-989-674-025-2
AU - Gawinecki M.
AU - Cabri G.
AU - Paprzycki M.
AU - Ganzha M.
PY - 2010
SP - 70
EP - 77
DO - 10.5220/0002809200700077