Hybrid Reasoning for Web Services Discovery

  • Mohamed Quafafou
  • Omar Boucelma
  • Yacine Sam
  • Zahi Jarir
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6799)


This paper describes a novel approach for discovering web services. The approach combines two logic-based formalisms and two reasoning engines and is illustrated in using a set of web services dedicated to web information extraction. The approach exhibits more or less complex relationships between services: (1) a service may have one or many variants, these are services that perform the same task, which leads to a first category of services specified with Feature Logics, (2) services may also be related by more intimate relationships, those links are expressed in using OIE ( Ontology for Information Extraction), a generic ontology that we designed. Hybrid reasoning is then performed based respectively on feature logics and OIE for Web services discovery.


Service Discovery Feature Term Variability Criterion Extraction Service Atomic Query 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Chang, C.-H., Lui, S.-C.: Iepad: information extraction based on pattern discovery. In: WWW, pp. 681–688 (2001)Google Scholar
  2. 2.
    Habegger, B., Quafafou, M.: Multi-pattern wrappers for relation extraction from the web. In: ECAI, pp. 395–399 (2002)Google Scholar
  3. 3.
    Horrocks, I., Sattler, U.: A tableaux decision procedure for shoiq. In: IJCAI, pp. 448–453 (2005)Google Scholar
  4. 4.
    Klusch, M., Fries, B., Sycara, K.P.: Automated semantic web service discovery with owls-mx. In: AAMAS, pp. 915–922 (2006)Google Scholar
  5. 5.
    Kopecký, J., Vitvar, T., Bournez, C., Farrell, J.: Sawsdl: Semantic annotations for wsdl and xml schema. IEEE Internet Computing 11(6), 60–67 (2007)CrossRefGoogle Scholar
  6. 6.
    Kushmerick, N.: Wrapper induction: Efficiency and expressiveness. Artif. Intell. 118(1-2), 15–68 (2000)MathSciNetCrossRefzbMATHGoogle Scholar
  7. 7.
    Küster, U., König-Ries, B., Stern, M., Klein, M.: Diane: an integrated approach to automated service discovery, matchmaking and composition. In: WWW, pp. 1033–1042 (2007)Google Scholar
  8. 8.
    Laender, A.H.F., Ribeiro-Neto, B.A., da Silva, A.S., Teixeira, J.S.: A brief survey of web data extraction tools. SIGMOD Record 31(2), 84–93 (2002)CrossRefGoogle Scholar
  9. 9.
    Martin, D.L., Burstein, M.H., McDermott, D.V., McIlraith, S.A., Paolucci, M., Sycara, K.P., McGuinness, D.L., Sirin, E., Srinivasan, N.: Bringing semantics to web services with owl-s. In: World Wide Web, pp. 243–277 (2007)Google Scholar
  10. 10.
    Roman, D., Keller, U., Lausen, H., de Bruijn, J., Lara, R., Stollberg, M., Polleres, A., Feier, C., Bussler, C., Fensel, D.: Web service modeling ontology. Applied Ontology 1(1), 77–106 (2005)Google Scholar
  11. 11.
    Sam, Y., Colonna, F.-M., Boucelma, O.: Customizable-resources description, selection, and composition: A feature logic based approach. In: Meersman, R., Tari, Z. (eds.) OTM 2006 Part-I. LNCS, vol. 4275, pp. 377–390. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  12. 12.
    Seo, H., Yang, J., Choi, J.: Knowledge-based Wrapper Generation by Using XML. In: IJCAI-2001 Workshop on Adaptive Text Extraction and Mining, Seattle,Washington (2001)Google Scholar
  13. 13.
    Smolka, G.: Feature-logik. In: GWAI, pp. 477–478 (1989)Google Scholar
  14. 14.
    Smolka, G.: Feature-constraint logics for unification grammars. J. Log. Program 12(1&2), 51–87 (1992)MathSciNetCrossRefzbMATHGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Mohamed Quafafou
    • 1
    • 2
  • Omar Boucelma
    • 1
    • 2
  • Yacine Sam
    • 3
  • Zahi Jarir
    • 4
  1. 1.Aix-Marseille Univ, LSISMarseilleFrance
  2. 2.CNRS, UMR 6168MarseilleFrance
  3. 3.François Rabelais UniversityToursFrance
  4. 4.Cadi Ayyad UniversityMarrakechMorocco

Personalised recommendations