• DocumentCode
    2325044
  • Title

    Mining sequences for patterns with non-repeating symbols

  • Author

    Walicki, Michal ; Ferreira, Diogo R.

  • Author_Institution
    Inst. of Inf., Univ. of Bergen, Bergen, Norway
  • fYear
    2010
  • fDate
    18-23 July 2010
  • Firstpage
    1
  • Lastpage
    8
  • Abstract
    Finding the case id in unlabeled event logs is arguably one of the hardest challenges in process mining research. While this problem can be addressed with greedy approaches, these usually converge to sub-optimal solutions. In this paper, we describe an approach to perform complete search over the search space. We formulate the problem as a matter of finding the minimal set of patterns contained in a sequence, where patterns can be interleaved but do not have repeating symbols. We show that for practical purposes it is possible to reduce the search space to maximal disjoint occurrences of these patterns. Experimental results suggest that, whenever this approach finds a solution, it usually finds a minimal one.
  • Keywords
    data mining; pattern recognition; sequences; system monitoring; complete search; greedy approach; nonrepeating symbols; process mining; search space; sequence pattern mining; unlabeled event logs;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Evolutionary Computation (CEC), 2010 IEEE Congress on
  • Conference_Location
    Barcelona
  • Print_ISBN
    978-1-4244-6909-3
  • Type

    conf

  • DOI
    10.1109/CEC.2010.5585995
  • Filename
    5585995