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Mining Popular Patterns from Transactional Databases

  • Carson Kai-Sang Leung
  • Syed K. Tanbeer
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7448)

Abstract

Since the introduction of the frequent pattern mining problem, researchers have extended frequent patterns to different useful patterns such as cyclic, emerging, periodic and regular patterns. In this paper, we introduce popular patterns, which captures the popularity of individuals, items, or events among their peers or groups. Moreover, we also propose (i) the Pop-tree structure to capture the essential information for the mining of popular patterns and (ii) the Pop-growth algorithm for mining popular patterns. Experimental results showed that our proposed tree structure is compact and space efficient and our proposed algorithm is time efficient.

Keywords

Data mining knowledge discovery interesting patterns popular patterns useful patterns tree-based mining 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Carson Kai-Sang Leung
    • 1
  • Syed K. Tanbeer
    • 1
  1. 1.University of ManitobaWinnipegCanada

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