Advertisement

A Hybrid Artificial Intelligent-Based Criteria-Matching with Classification Algorithm

  • Alex T. H. Sim
  • Vincent C. S. Lee
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3614)

Abstract

Classifying dynamic behavioural based events, for example human behaviour profile, is a non-trivial task. In this paper, we propose an AI-based criteria-matching with classification algorithm which can be used to classify preference based decision outcome. The proposed algorithm is mathematically justified and with more practical benefits than a conventional multivariate discriminant analysis algorithm which is widely used for prediction tasks. Real world (Singapore) diamond dataset test results revealed the practical usefulness of our proposed algorithm to diamond sellers in Singapore.

Keywords

Training Data Classification Algorithm Classification Rule Market Segmentation Customer Group 
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.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Smith, W.: Product Differentiation and Market Segmentation as Alternative Marketing Strategies. Journal of Marketing 21, 3–8 (1956)CrossRefGoogle Scholar
  2. 2.
    Sim, A.T.H.: A Technique Integrating Criteria-matching with Classification for Predicting Customer Groups. Thesis, Monash University, pp.1–229 (2004)Google Scholar
  3. 3.
    Zeng, Z., Yan, H.: Region Matching by Optimal Fuzzy Dissimilarity. In: Proceedings of the ACM International Conference Proceeding Series: Pan-Sydney workshop on Visualisation, pp. 75–84. Australian Computer Society Inc, Australia (2000)Google Scholar
  4. 4.
    Zeng, Z., Yan, H.: Region Matching and Optimal Matching Pair Theorem. In: Proceedings of International Conference on Computer Graphics, pp. 232–239. IEEE Computer Society, Washington (2001)Google Scholar
  5. 5.
    Khan, M., Ding, Q., Perrizo, W.: k-nearest Neighbor Classification on Spatial Data Streams Using P-trees. In: Proceedings of the Pacific-Asia Conference on Knowledge Discovery and Data Mining, CiteSeer, pp. 517–518 (2002)Google Scholar
  6. 6.
    Chu, S.: Pricing the C’s of Diamond Stones. Journal of Statistics Education 9(2) (2001) (On-line)Google Scholar
  7. 7.
    Chard: The Very Highest Quality Diamond Information. Available: (February 1 2004), http://www.24carat.co.uk/diamondscolour.html
  8. 8.
    The, A.D.H.C.: HRD Diamond Certificate (February 1 2004)Available, http://www.diamonds.be/professional/certificate/dia_certi.htm
  9. 9.
    Chu, S.: Diamond Ring Pricing Using Linear Regression. Journal of Statistics Education 4(3) (1996) (On-line)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Alex T. H. Sim
    • 1
  • Vincent C. S. Lee
    • 1
  1. 1.School of Business SystemsMonash UniversityClaytonAustralia

Personalised recommendations