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A novel algorithm for extracting knowledge based on mining multi-level sequential patterns

Listed author(s):
  • Negar Gh Ghanbari
  • Mohammad Reza Gholamian
Registered author(s):

    In this paper, we consider the problem of finding sequential patterns in multi-levels, with aid of candidate generate and test approach. Based on this technique, many sequential pattern algorithms have been developed, but few of them have paid attention to multi-level concept. We thus purpose a new efficient algorithm, called dynamic vertices levelwise (DVlw) for mining multi-level sequence patterns. It uses the same principals as other candidate generation and test algorithms but handles multi-levelled property for sequences prior to and separately from the testing and counting steps of candidate sequences. Empirical evaluation using synthetic data indicates that the proposed algorithm performs significantly faster than a state-of-the-art algorithm with this approach.

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    Article provided by Inderscience Enterprises Ltd in its journal Int. J. of Business and Systems Research.

    Volume (Year): 6 (2012)
    Issue (Month): 3 ()
    Pages: 269-278

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    Handle: RePEc:ids:ijbsre:v:6:y:2012:i:3:p:269-278
    Contact details of provider: Web page: http://www.inderscience.com/browse/index.php?journalID=206

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