Is Frequency Enough for Decision Makers to Make Decisions?

  • Shichao Zhang
  • Jeffrey Xu Yu
  • Jingli Lu
  • Chengqi Zhang
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3918)

Abstract

There are many advanced techniques that can efficiently mine frequent itemsets using a minimum support. However, the question that remains unanswered is whether the minimum support can really help decision makers to make decisions. In this paper, we study four summary queries for frequent itemsets mining, namely, 1) finding a support-average of itemsets, 2) finding a support-quantile of itemsets, 3) finding the number of itemsets that greater/less than the support-average, i.e., an approximated distribution of itemsets, and 4) finding the relative frequency of an itemset. With these queries, a decision maker will know whether an itemset in question is greater/less than the support-quantile; the distribution of itemsets; and the frequentness of an itemset. Processing these summary queries is challenging, because the minimum-support constraint cannot be used to prune infrequent itemsets.

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References

  1. [Roddick&Rice 2001]
    Roddick, J.F., Rice, S.: What’s Interesting About Cricket? – On Thresholds and Anticipation in Discovered Rules. SIGKDD Explorations 3(1), 1–5 (2001)CrossRefGoogle Scholar
  2. [Wang et al 2001]
    Wang, K., He, Y., Cheung, D., Chin, F.: Mining Confident Rules without Support Requirement. In: Proceedings of CIKM, Atlanta (2001)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Shichao Zhang
    • 1
  • Jeffrey Xu Yu
    • 2
  • Jingli Lu
    • 3
  • Chengqi Zhang
    • 1
  1. 1.University of Technology SydneyAustralia
  2. 2.Chinese University of Hong KongChina
  3. 3.Monash UniversityAustralia

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