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Shaping a CBR view with XML

  • Conor Hayes
  • Padraig Cunningham
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1650)

Abstract

Case Based Reasoning has found increasing application on the Internet as an assistant in Internet commerce stores and as a reasoning agent for online technical support. The strength of CBR in this area stems from its reuse of the knowledge base associated with a particular application, thus providing an ideal way to make personalised configuration or technical information available to the Internet user. Since case data may be one aspect of a company’s entire corporate knowledge system, it is important to integrate case data easily within a company’s IT infrastructure, using industry specific vocabulary. We suggest XML as the likely candidate to provide such integration. Some applications have already begun to use XML as a case representation language. We review these and present the idea of a standard case view in XML that can work with the vocabularies or namespaces being developed by specific industries. Earlier research has produced version 1.0 of a Case Based Mark-up Language which attempts to mark-up cases in XML to enable distributed computing. The drawbacks of this implementation are outlined in this paper as well as the developments in XML that allow us to produce an XML “View” of a company’s knowledge system. We will detail the benefits of our system for industry in general in terms of extensibility, ease of reuse and interoperability.

Keywords

Real Estate Case Schema Case Base Reasoning System Internet Commerce Real Estate Listing 
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.

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References

  1. [1]
    Boumphrey, F. et al. (1998) XML Applications, Wrox Press, pgs. 97–130Google Scholar
  2. [2]
    Cunningham P., Finn. D., Slattery, S. (1994) Knowledge Engineering requirements in Derivational Analogy in Topics in Case Based Reasoning, Lecture notes in Artificial Intelligence, S. Wess, K-D Althoff, M.M Richter eds., pp234–245, Springer Verlag, 1994Google Scholar
  3. [3]
    Doyle, M., Ferrario, M.A, Hayes, C., Cunningham, P., Smyth, B. (1998) CBR Net: Smart Technology Over a Network. TCD Technical Report TCD-CS-1998-07-available at http://www.cs.tcd.ie/publications/tech-reports/trindex.98.html
  4. [4]
    Gentner, D., and Forbus, K.D.1991. MAC/FAC: A model of similarity based access and mapping. In Proceedings of the Thirteenth Annual Conference of the Cognitive Science Society. Northvale, NJ: ErlbaumGoogle Scholar
  5. [5]
    Gardingen D., Watson I. (1998). A Web based Case-Based Reasoning System for HVAC Sales Support. Proceedings of British Expert Systems conference 1998.Google Scholar
  6. [6]
    Hanney, K 1996. Learning Adaptation Rules From Cases. MSc. Thesis. Computer Science Department, Trinity College Dublin.Google Scholar
  7. [7]
    Hayes C., Cunningham P., Doyle M. (1998) Distributed CBR using XML in proceedings of the Workshop: Intelligent Systems and Electronic Commerce, Bremen, September 15-17 1998. Also available as TCD technical report TCDCS-1998-06 http://www.cs.tcd.ie/publications/tech-reports/tr-index.98.html
  8. [8]
    INRECA consortium.(1994). Casuel: A Common Case Representation Language, available at http://wwwagr.informatik.unikl.de/~bergmann/casuel/CASUEL_toc2.04.fm.htmlGoogle Scholar
  9. [9]
    Kitano, H. & Shimazu, H. (1996) The Experience Sharing Architecture: ACase Study in Corporate-Wide Case-Based Software Quality Control. In Case-Based Reasoning: Experiences, Lessons & Future Directions. Leake, D.B. (Ed.) pp 235–268. AAAI Press/The MIT Press Menlo Park, Ca, US.Google Scholar
  10. [10]
    Shimazu, H. (1998). Textual Case Based Reasoning using XML on the Worldwide Web in Advances in Case Based Reasoning, proceedings of 4thEuropean workshop on CBR (EWCBR), Springer Verlag LNAIGoogle Scholar
  11. [11]
    Wilke, W., Lenz, M., Wess, S. (1998). Intelligent Sales Support with CBR. In Case-Based Reasoning Technology: from foundations to applications. Lenz, M., Bartsch-Sporl, B., Burkhard. H-D & Wess, S. (Eds.). Lecture Notes in AI#1400 91–113. Springer-Verlag, Berlin.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1999

Authors and Affiliations

  • Conor Hayes
    • 1
  • Padraig Cunningham
    • 1
  1. 1.Department of Computer ScienceTrinity CollegeDublin

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