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Extracting Sequential Patterns Based on User Defined Criteria

  • Oznur Kirmemis Alkan
  • Pınar Karagoz
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8073)

Abstract

Sequential pattern extraction is essential in many applications like bioinformatics and consumer behavior analysis. Various frequent sequential pattern mining algorithms have been developed that mine the set of frequent subsequences satisfying a minimum support constraint in a transaction database. In this paper, a hybrid framework to sequential pattern mining problem is proposed which combines clustering together with a novel pattern extraction algorithm that is based on an evaluation function, which utilizes user-defined criteria to select patterns. The proposed solution is applied on Web log data and Web domain, however, it can work in any other domain that involves sequential data as well. Through experimental evaluation on two different datasets, we show that the proposed framework can achieve valuable results for extracting patterns under user defined selection criteria.

Keywords

equential Pattern User-defined selection criteria Clustering PatternFindBF Web Usage Pattern 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Oznur Kirmemis Alkan
    • 1
  • Pınar Karagoz
    • 1
  1. 1.Computer Engineering DepartmentMiddle East Technical University (METU)AnkaraTurkey

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