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    A process mining technique using pattern recognition

    Liesaputra, Veronica; Yongchareon, Dr. Sira; Chaisiri, Sivadon

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    Process mining - CAiSE Forum.pdf (268.9Kb)
    Date
    2015-06
    Citation:
    Liesaputra, V., Yongchareon, S., & Chaisiri, S. (2015, June). A Process Mining Technique Using Pattern Recognition. In J. Grabis and K. Sandkuhl (Ed.), Proceedings of the CAiSE Forum, 27th International Conference on Advanced Information Systems Engineering (CAiSE) (pp.57-64)
    Permanent link to Research Bank record:
    https://hdl.handle.net/10652/3362
    Abstract
    Several works have proposed process mining techniques to discover process models from event logs. With the existing works, mined models can be built based on analyzing the relationship between any two events seen in event logs. Being restricted by that, they can only handle special cases of routing constructs and often produce unsound models that do not cover all of the traces in the logs. In this paper, we propose a novel technique for process mining based on using a pattern recognition technique called Maximal Pattern Mining (MPM). Our MPM technique can handle loops (of any length), duplicate tasks, non-free choice constructs, and long distance dependencies. Furthermore, by using the MPM, the discovered models are generally much easier to understand.
    Keywords:
    Maximal Pattern Mining (MPM), process mining, discovery algorithms
    ANZSRC Field of Research:
    080109 Pattern Recognition and Data Mining
    Copyright Holder:
    Conference on Advanced Information Systems Engineering (CAiSE)
    Available Online at:
    http://caise2015.dsv.su.se/
    Rights:
    This digital work is protected by copyright. It may be consulted by you, provided you comply with the provisions of the Act and the following conditions of use: Any use you make of these documents or images must be for research or private study purposes only, and you may not make them available to any other person. You will recognise the author's and publishers rights and give due acknowledgement where appropriate.
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