An Auction-Based Semantic Service Discovery Model for E-Commerce Applications

  • Vedran Podobnik
  • Krunoslav Trzec
  • Gordan Jezic
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4277)

Abstract

Mediation between buyers (service requester’s agents) and sellers (service provider’s agents) is one of the most difficult problems in real electronic markets. In this paper, we propose an economic approach to solving this problem combined with AI (Artificial Intelligence) concepts. Firstly, we enable provider agents to dynamically and autonomously advertise semantic descriptions of available services by proposing a new auction model based on Pay-Per-Click advertising auctions. We call it the Semantic Pay-Per-Click Agent (SPPCA) auction. Requester agents then use two-level filtration of the advertised services to efficiently discover eligible services. In the first level of filtration, a semantic-based mechanism for matchmaking between services requested by buyers and those advertised by sellers is applied. Services which pass the first level of filtration are then considered on the second level. Here information regarding the actual performance of service providers is considered in conjunction with the prices bid by service provider’s agents in the SPPCA auction. A final set of advertised services is then chosen and proposed to the buyer agent as an answer to its request.

Keywords

Intelligent software agents Web services the semantic Web OWL-S Pay-Per-Click (PPC) auctions digital economy electronic commerce 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Carlson, B.: The Digital Economy – What is New and What is Not? In: Structural Change and Economic Dynamics, vol. 15, pp. 245–264. Elsevier, Amsterdam (2004)Google Scholar
  2. 2.
    Wurman, P.R., Wellman, M.P., Walsch, W.E.: Specifying Rules for Electronic Auctions. AI Magazine, American Association for Artificial Intelligence 23(3), 15–24 (2002)Google Scholar
  3. 3.
    Podobnik, V., Jezic, G., Trzec, K.: An Agent-mediated Electronic Market of Semantic Web Services. In: Proc. of the AAMAS Workshop on Business Agents and the Semantic Web (BASeWEB), Hakodate, Japan, pp. 1–10 (2006)Google Scholar
  4. 4.
    Srinivasan, N., Paolucci, M., Sycara, K.: An Efficient Algorithm for OWL-S Based Semantic Search in UDDI. In: Proc. of the 1st Int. Workshop on Semantic Web Services and Web Process Composition (SWSWPC), San Diego, CA, USA, pp. 96–110 (2004)Google Scholar
  5. 5.
    Lim, W.S., Tang, C.S.: An Auction Model Arising from an Internet Search Service Provider. European Journal of Operational Research 172, 956–970 (2006)MATHCrossRefMathSciNetGoogle Scholar
  6. 6.
    Luan, X.: Adaptive Middle Agent for Service Matching in the Semantic Web – A Quantitive Approach. Thesis, University of Maryland Baltimore County (2004)Google Scholar
  7. 7.
    de Brujin, J., Fensel, D., Keller, U., Lara, R.: Using the Web Service Modeling Ontology to Enable Semantic E-business. Communications of the ACM 48(12), 43–47 (2005)CrossRefGoogle Scholar
  8. 8.
    W3C Web service architecture: http://www.w3.org/TR/ws-arch/
  9. 9.
    Berners-Lee, T., Hendler, J., Lassila, O.: The Semantic Web. Scientific American 284(5), 34–43 (2001)CrossRefGoogle Scholar
  10. 10.
    Singh, R., Iyer, L.S., Salam, A.F.: The Semantic E-business Vision. Communications of the ACM 48(12), 38–41 (2005)CrossRefGoogle Scholar
  11. 11.
    Hendler, J.: Agents and the Semantic Web. IEEE Intelligent Systems 16(2), 30–37 (2001)CrossRefGoogle Scholar
  12. 12.
    Podobnik, V.: Software Agents for Electronic Market. Thesis, University of Zagreb, Faculty of Electrical Engineering and Computing (in Croatian) (2006)Google Scholar
  13. 13.
    Bradshaw, J.M.: Software Agents. MIT Press, Cambridge (1997)Google Scholar
  14. 14.
    Tang, S.: Matching of Web Services Specifications using DAML-S Descriptions. Thesis, Technical University of Berlin (2004)Google Scholar
  15. 15.
    Sycara, K., Paolucci, M., Anolekar, A., Srinivasan, N.: Automated Discovery, Interaction and Composition of Semantic Web Services. Journal of Web Semantics 1(1) (2004)Google Scholar
  16. 16.
    Li, L., Horrock, I.: A Software Framework for Matchmaking Based on Semantic Web Technology. In: Proc. of the 12th Int. World Wide Web Conference (WWW), pp. 331–339. Budapest, Hungary (2003)Google Scholar
  17. 17.
    Colucci, S., Noia, T.D., Sciascio, E.D., Donini, F., Mongiello, M.: Concept Abduction and Contraction for Semantic-based Discovery of Matches and Negotiation Spaces in an E-marketplace. Electronic Commerce Research and Applications 4(3), 345–361 (2005)CrossRefGoogle Scholar
  18. 18.
    Keller, U., Lara, R., Lausen, H., Polleres, A., Fensel, D.: Automatic Location of Services. In: Gómez-Pérez, A., Euzenat, J. (eds.) ESWC 2005. LNCS, vol. 3532, pp. 1–16. Springer, Heidelberg (2005)CrossRefGoogle Scholar
  19. 19.
    Klusch, M., Fries, B., Sycara, K.: Automated Semantic Web Service Discovery with OWLS-MX. In: Proc. of the 5th Int. Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS), Hakodate, Japan, pp. 915–922 (2006)Google Scholar
  20. 20.
    Kitts, B., LeBlanc, B.: Optimal Bidding on Keyword Auctions. Electronic Markets 14(3), 186–201 (2004)CrossRefGoogle Scholar
  21. 21.
    Aggarwal, G., Goel, A., Motwani, R.: Truthful Auctions for Pricing Search Keywords. In: Proc. of the 7th ACM Conference on Electronic Commerce (EC), Ann Arbor, Michigan, USA (2006)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Vedran Podobnik
    • 1
  • Krunoslav Trzec
    • 2
  • Gordan Jezic
    • 1
  1. 1.Faculty of Electrical Engineering and Computing, Department of TelecommunicationsUniversity of ZagrebZagrebCroatia
  2. 2.Ericsson Nikola TeslaR&D CenterZagrebCroatia

Personalised recommendations