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Case-Based Reasoning for Candidate List Extraction in a Marketing Domain.

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Case-Based Reasoning Research and Development (ICCBR 1999)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 1650))

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Abstract

This paper describes a software tool called CALIBRE (Candidate Library Retrieval). The tool incorporates case-base reasoning to support the extraction of candidate lists for targeted marketing campaigns. The tool has been aimed at users in the marketing domain. This domain is characterised by very large databases containing many Terabytes of customer related information. Large systems such as these require careful management of the queries being submitted to optimise the use of processing and storage resources. The CBR approach encourages consistent best practice as well as cutting down on valuable negotiation time. An early prototype has been built and is currently used for experimental purposes.

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References

  1. Aamodt, A., Plaza, E.: Case-Based Reasoning: Foundational Issues, methodological Variations, and System Approaches. AI Communications 7(1), 39–52, 1994

    Google Scholar 

  2. Leake, D.: Case-Based Reasoning: Experiences, Lessons, & Future Directions. AAAI Press, ISBN 0-262-62110-X LEACP, 1997

    Google Scholar 

  3. Piatetsky-Shapiro, G., Frawley, W.J. (eds), Knowledge Discovery in Databases, AAAI Press, 1991.

    Google Scholar 

  4. Ribeiro, J.S., Kaufmann, K.A., Kerschberg, L., ‘Knowledge Discovery from Multiple Databases’, in KDD-95: Proc. of the 1st Int’l Conf. on Knowledge Discovery and Data Mining, U.M. Fayyad, R. Uthurusamy (eds.), AAAI Press, 1995, pp240–245.

    Google Scholar 

  5. Brightware Inc (1996). ARTScript Programming Guide 3, Rules & CBR

    Google Scholar 

  6. Brown, M. (1993). A Memory model for Case Retrieval by Activation Passing, Department of Computer Science, Manchester University.

    Google Scholar 

  7. Everitt, B.S. (1980), ‘Cluster Analysis’, 2d Edition, London: Heineman Educational Books Ltd

    MATH  Google Scholar 

  8. Fagan, M, Corley S L, ‘CBR for the Reuse of Corporate SQL Knowledge’ in Advances in Case-Based Reasoning, EWCBR-98. Springer-Verlag, pp382–391.

    Google Scholar 

  9. Schank, R.C., Abelson, R. (1977) Scipts, Plans; Goals and Understanding: An Inquiry into Human Knowledge Structures.

    Google Scholar 

  10. SAS, http://www.sas.com/

  11. Richard Stevens, W. (1990). UNIX Network Programming, Prentice-Hall.

    Google Scholar 

  12. Kitano, H., Shibata, A., Shimazu, H., Kajihara, J., & Sato, A. (1992) Building large-scale and corporate wide case-based systems In, Proceedings of AAAI-92

    Google Scholar 

  13. Netten, B.D., & Vingerhoeds, R.A. (1995) Large-scale fault diagnosis for on-board train systems In, Case-Based Reasoning Research and Development

    Google Scholar 

  14. Waltz, D. (1996) Large-Scale Applications of CBR In, Advances in Case-Based Reasoning

    Google Scholar 

  15. Schaaf, J.W (1996) Fish and Shrink: A Next Step Towards Efficient Case Retrieval in Large-Scale Case Bases In, Advances in Case-Based Reasoning

    Google Scholar 

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Author information

Authors and Affiliations

  1. BT Laboratories, Martlesham Heath Ipswich, Suffolk, IP5 3RE, UK

    Michael Fagan & Konrad Bloor

Authors
  1. Michael Fagan
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  2. Konrad Bloor
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Editor information

Editors and Affiliations

  1. Fraunhofer Institute for Experimental Software Engineering (IESE), Sauerwiesen 6, D 67661, Kaiserslautern, Germany

    Klaus-Dieter Althoff

  2. Department of Computer Science, University of Kaiserslautern, P.O. Box 3049, D 67653, Kaiserslautern, Germany

    Ralph Bergmann

  3. Department of Computer Science, University of Wyoming, P.O. Box 3682, Laramie, WY, 82072, USA

    L.Karl Branting

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© 1999 Springer-Verlag Berlin Heidelberg

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Fagan, M., Bloor, K. (1999). Case-Based Reasoning for Candidate List Extraction in a Marketing Domain.. In: Althoff, KD., Bergmann, R., Branting, L. (eds) Case-Based Reasoning Research and Development. ICCBR 1999. Lecture Notes in Computer Science, vol 1650. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-48508-2_31

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  • DOI: https://doi.org/10.1007/3-540-48508-2_31

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-66237-2

  • Online ISBN: 978-3-540-48508-7

  • eBook Packages: Springer Book Archive

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