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COBRA: Closed Sequential Pattern Mining Using Bi-phase Reduction Approach

  • Kuo-Yu Huang
  • Chia-Hui Chang
  • Jiun-Hung Tung
  • Cheng-Tao Ho
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4081)

Abstract

In this work, we study the problem of closed sequential pattern mining. We propose a novel approach which extends a frequent sequence with closed itemsets instead of single items. The motivation is that closed sequential patterns are composed of only closed itemsets. Hence, unnecessary item extensions which generates non-closed sequential patterns can be avoided. Experimental evaluation shows that the proposed approach is two orders of magnitude faster than previous works with a modest memory cost.

Keywords

Sequential Pattern Pattern Mining Frequent Itemsets Sequence Extension Sequential Pattern Mining 
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

  • Kuo-Yu Huang
    • 1
  • Chia-Hui Chang
    • 1
  • Jiun-Hung Tung
    • 1
  • Cheng-Tao Ho
    • 1
  1. 1.Department of Computer Science and Information EngineeringNational Central UniversityChung-LiTaiwan

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