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PrefixTreeESpan: A Pattern Growth Algorithm for Mining Embedded Subtrees

  • Lei Zou
  • Yansheng Lu
  • Huaming Zhang
  • Rong Hu
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4255)

Abstract

Frequent embedded subtree pattern mining is an important data mining problem with broad applications. In this paper, we propose a novel embedded subtree mining algorithm, called PrefixTreeESpan (i.e. Prefix-Tree-projected Embedded-Subtree pattern), which finds a subtree pattern by growing a frequent prefix-tree. Thus, using divide and conquer, mining local length-1 frequent subtree patterns in Prefix-Tree-Projected database recursively will lead to the complete set of frequent patterns. Different fromChopper and XSpanner [4], PrefixTreeESpan does not need a checking process. Our performance study shows that PrefixTreeESpan outperforms Apriori-like algorithm: TreeMiner [6], and pattern-growth algorithms :Chopper , XSpanner .

Keywords

Frequent Pattern Pattern Mining Prefix Tree Growth Element Tree Database 
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.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Lei Zou
    • 1
  • Yansheng Lu
    • 1
  • Huaming Zhang
    • 2
  • Rong Hu
    • 1
  1. 1.HuaZhong University of Science and TechnologyWuhanP.R. China
  2. 2.The University of Alabama in HuntsvilleHuntsvilleUSA

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