Realistic Synthetic Data for Testing Association Rule Mining Algorithms for Market Basket Databases

  • Colin Cooper
  • Michele Zito
Conference paper

DOI: 10.1007/978-3-540-74976-9_39

Part of the Lecture Notes in Computer Science book series (LNCS, volume 4702)
Cite this paper as:
Cooper C., Zito M. (2007) Realistic Synthetic Data for Testing Association Rule Mining Algorithms for Market Basket Databases. In: Kok J.N., Koronacki J., Lopez de Mantaras R., Matwin S., Mladenič D., Skowron A. (eds) Knowledge Discovery in Databases: PKDD 2007. PKDD 2007. Lecture Notes in Computer Science, vol 4702. Springer, Berlin, Heidelberg

Abstract

We investigate the statistical properties of the databases generated by the IBM QUEST program. Motivated by the claim (also supported empirical evidence) that item occurrences in real life market basket databases follow a rather different pattern, we propose an alternative model for generating artificial data.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Colin Cooper
    • 1
  • Michele Zito
    • 2
  1. 1.Department of Computer Science, Kings’ College, London WC2R 2LSUK
  2. 2.Department of Computer Science, University of Liverpool, Liverpool, L69 3BXUK

Personalised recommendations