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Min-Max Itemset Trees for Dense and Categorical Datasets

  • Jennifer Lavergne
  • Ryan Benton
  • Vijay V. Raghavan
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7661)

Abstract

The itemset tree data structure is used in targeted association mining to find rules within a user’s sphere of interest. In this paper, we propose two enhancements to the original unordered itemset trees. The first enhancement consists of sorting all nodes in lexical order based upon the itemsets they contain. In the second enhancement, called the Min-Max Itemset Tree, each node was augmented with minimum and maximum values that represent the range of itemsets contained in the children below. For demonstration purposes, we provide a comprehensive evaluation of the effects of the enhancements on the itemset tree querying process by performing experiments on sparse, dense, and categorical datasets.

Keywords

data mining association mining targeted association mining itemset tree min-max itemset tree dense data categorical data 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Jennifer Lavergne
    • 1
  • Ryan Benton
    • 1
  • Vijay V. Raghavan
    • 1
  1. 1.The Center for Advanced Computer StudiesUniversity of Louisiana at LafayetteLafayetteUSA

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