Semantic Annotation of Web Services: A Comparative Study

  • Djelloul Bouchiha
  • Mimoun Malki
  • Djihad Djaa
  • Abdullah Alghamdi
  • Khalid Alnafjan
Conference paper
Part of the Studies in Computational Intelligence book series (SCI, volume 492)


A Web service is software that provides its functionality through the Web using a common set of technologies, including SOAP, WSDL and UDDI. This allows access to software components residing on different platforms and written in different programming languages. However, several spots, including the service discovery and composition, remain difficult to be automated. Thus, a new technology has emerged to help automate these tasks ; it is the Semantic Web Services (SWS). One solution to the engineering of SWS is the annotation. In this paper, an approach for annotating Web services is presented. The approach consists of two processes, namely the categorization and matching. Both processes use ontology matching techniques. In particular, the two processes use similarity measures between entities, strategies for computing similarities between sets and a threshold corresponding to the accuracy. Thus, an internal comparative study has been done to answer the questions: which strategy is appropriate to this approach? Which measure gives best results? And which threshold is optimum for the selected measure and strategy? An external comparative study is also useful to prove the efficacy of this approach compared to existing annotation approaches.


Annotation Web Service SAWSDL Semantic Web Services Ontology Matching 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Baeze-Yates, R., Ribeiro-Neto, B.: Modern information retrieval. Addison-Wesley, ACM Press, Reading, MA (1999)Google Scholar
  2. 2.
    Belhajjame, K., Embury, S.M., Paton, N.W., Stevens, R., Goble, C.A.: Automatic annotation of web services based on workflow definitions. ACM Transactions on the Web (TWEB Journal) 2(2) (2008)Google Scholar
  3. 3.
    Bouchiha, D., Malki, M.: Semantic Annotation of Web Services. In: 4th International conference on Web and Information Technologies (ICWIT 2012), SBA Algeria, April 29-30 (2012)Google Scholar
  4. 4.
    Bowers, S., Ludäscher, B.: A calculus for propagating semantic annotations through scientific workflow queries. In: Query Languages and Query Processing workshop (QLQP-2006) anised in conjunction with the 10th International Conference on Extending abase Technology, pp. 712–723 (2006)Google Scholar
  5. 5.
    Carman, M.J., Knoblock, C.A.: Learning Semantic Definitions of Online Information Sources. Journal of Artificial Intelligence Research 30, 1–50 (2007)MATHGoogle Scholar
  6. 6.
    Cui, H.: CharaParser for fine-grained semantic annotation of organism morphological descriptions. Journal of the American Society for Information Science and Technology 63(4), 738–754 (2012)CrossRefGoogle Scholar
  7. 7.
    Euzenat, J., Shvaiko, P.: Ontology Matching. English book. Springer, Heidelberg (2007)MATHGoogle Scholar
  8. 8.
    Farrell, J., Lausen, H.: Semantic Annotations for WSDL and XML Schema. W3C Recommendation (2007), (accessed August 28, 2007)
  9. 9.
    Grcar, M., Mladenic, D.: Visual OntoBridge: Semi-automatic Semantic Annotation Software. In: Buntine, W., Grobelnik, M., Mladenić, D., Shawe-Taylor, J. (eds.) ECML PKDD 2009, Part II. LNCS, vol. 5782, pp. 726–729. Springer, Heidelberg (2009)CrossRefGoogle Scholar
  10. 10.
    Hess, A., Johnston, E., Kushmerick, N.: ASSAM: A Tool for Semi-Automatically Annotating Semantic Web Services. In: International Semantic Web Conference, Hiroshima Japan, pp. 320–335 (2004)Google Scholar
  11. 11.
    Jonquet, C., Shah, N., Youn, C., Musen, M., Callendar, C., Storey, M.: NCBO Annotator: Semantic Annotation of Biomedical Data. In: 8th International Semantic Web Conference (ISWC 2009) Posters and Demonstrations, Washington DC, USA (2009)Google Scholar
  12. 12.
    Larsen, B., Aone, C.: Fast and effective text mining using lineartime document clustering. In: Proceedings of the 5th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 16–22 (1999)Google Scholar
  13. 13.
    Lerman, K., Plangprasopchok, A., Knoblock, C.A.: Automatically labeling the inputs and outputs of web services. In: Proceedings of the National Conference on Artificial Intelligence (AAAI 2006), Boston, Massachusetts, USA (2006)Google Scholar
  14. 14.
    Liao, Y., Lezoche, M., Panetto, H., Boudjlida, N.: Semantic Annotation Model Definition for Systems Interoperability. In: The 6th International Workshop on Enterprise Integration, Interoperability and Networking (EI2N), Hersonissos Crete, Greece (2011)Google Scholar
  15. 15.
    Miller, G.A.: WordNet: An on-line lexical database. International Journal of Lexicography, 235–312 (1990)Google Scholar
  16. 16.
    Patil, A., Oundhakar, S., Sheth, A., Verma, K.: METEOR-S Web Service Annotation Framework. In: WWW 2004, pp. 553–562. ACM Press (2004)Google Scholar
  17. 17.
    Pedersen, T., Patwardhan, S., Michelizzi, J.: WordNet:Similarity - Measuring the Relatedness of Concepts. In: Proceedings of the Nineteenth National Conference on Artificial Intelligence (AAAI 2004), pp. 1024–1025 (2004)Google Scholar
  18. 18.
    Pustejovsky, J., Lee, K., Bunt, H., Romary, L.: ISO-TimeML: An International Standard for Semantic Annotation. In: Proceedings LREC 2010, La Valette Malte (2010)Google Scholar
  19. 19.
    Wyner, A., Peters, W.: Semantic Annotations for Legal Text Processing using GATE Teamware. In: The 4th Workshop on Semantic Processing of Legal Texts (SPLeT 2012) in Istanbul Turkey (2012)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2013

Authors and Affiliations

  • Djelloul Bouchiha
    • 1
  • Mimoun Malki
    • 1
  • Djihad Djaa
    • 2
  • Abdullah Alghamdi
    • 3
  • Khalid Alnafjan
    • 3
  1. 1.EEDIS LaboratoryDjillali Liabes University of Sidi Bel AbbesSidi Bel AbbesAlgeria
  2. 2.Computer DepartmentUniversity Dr. Taher MoulaySaidaAlgeria
  3. 3.College of Computer and Information SciencesKSURiyadhSaudi Arabia

Personalised recommendations