A Semantic Scoring Approach for Service Offers

  • Ikbel Guidara
  • Kaouthar Fakhfakh
  • Tarak Chaari
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7387)

Abstract

Automating service selection using semantic approaches have been extensively studied in recent years. In fact, given the big number of provider offers, sourcing of the most relevant service to the client intentions is a complex task especially when providers and customers don’t share the same knowledge degree. In particular, differentiating between very similar offers satisfying the same number of client constraints is still a challenging task. In this paper, we present a novel semantic scoring approach that helps clients to select the most appropriate service offer according to their intentions. Our approach detects direct and indirect semantic correspondences between these intentions and the available offers using ontological models. It fairly evaluates these offers and ranks them according to their semantic closeness to the client intentions taking into account both functional and QoS properties. Our ranking is based on a deep examination of provider offers and can distinguish between services that look the same for non expert clients.

Keywords

Ontologies Quality of Service (QoS) Semantic Web Service Sourcing 

References

  1. 1.
    Kaouthar, F., Tarak, C., Saïd, T., Mohamed, J., Khalil, D.: ODACE SLA: Ontology Driven Approach for Automatic Establishment of Service Level Agreements. IJSSOE 1(3), 1–20 (2010)Google Scholar
  2. 2.
    Lamparter, S., Ankolekar, A., Studer, R., Grimm, S.: Preference based selection of highly configurable web services. In: Proceedings of the 16th International Conference on the World Wide Web WWW 2007, pp. 1013–1022 (2007)Google Scholar
  3. 3.
    Wang, X., Vitvar, T., Kerrigan, M., Toma, I.: A QoS-Aware Selection Model for Semantic Web Services. In: Dan, A., Lamersdorf, W. (eds.) ICSOC 2006. LNCS, vol. 4294, pp. 390–401. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  4. 4.
    Zeng, L.Z., Benatallah, B., Ngu, A.H.H.: QoS-aware middleware for Web services composition. IEEE Transaction on Software Engineering 30(5), 311–327 (2004)CrossRefGoogle Scholar
  5. 5.
    Andrikopoulos, V., Fugini, M., Papazoglou, M., Parkin, M., Pernici, B., Siadat, S.H.: QoS Contract Formation and Evolution. In: Proceedings of the 11th International Conference on Electronic Commerce and Web Technologies (EC-WEB 2010), pp. 119–130 (2010)Google Scholar
  6. 6.
    Comuzzi, M., Pernici, B.: A framework for QoS-based Web service contracting. ACM Transactions on the Web (TWEB) 3(3) (June 2009)Google Scholar
  7. 7.
    Marco, L.S., David, M., Claude, M.: Discovering Semantic Web services using SPARQL and intelligent agents. Journal of Web Semantics 8, 310–328 (2010)CrossRefGoogle Scholar
  8. 8.
    van Rijsbergen, C.J.: Getting into Information Retrieval. In: Agosti, M., Crestani, F., Pasi, G. (eds.) ESSIR 2000. LNCS, vol. 1980, pp. 1–20. Springer, Heidelberg (2001)CrossRefGoogle Scholar
  9. 9.
    Siddharth, P.: Incorporating dictionary and corpus information into a context vector measure of semantic relatedness. Master’s thesis, University of Minnesota, Duluth (2003)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Ikbel Guidara
    • 1
  • Kaouthar Fakhfakh
    • 1
  • Tarak Chaari
    • 1
  1. 1.ReDCAD LaboratoryUniversity of SfaxSfaxTunisia

Personalised recommendations