Recurrent process mining with live event data

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    3 Citations (Scopus)
    3 Downloads (Pure)

    Abstract

    In organizations, process mining activities are typically performed in a recurrent fashion, e.g. once a week, an event log is extracted from the information systems and a process mining tool is used to analyze the process’ characteristics. Typically, process mining tools import the data from a file-based source in a pre-processing step, followed by an actual process discovery step over the pre-processed data in order to present results to the analyst. As the amount of event data grows over time, these tools take more and more time to do pre-processing and all this time, the business analyst has to wait for the tool to finish. In this paper, we consider the problem of recurrent process discovery in live environments, i.e. in environments where event data can be extracted from information systems near real time. We present a method that pre-processes each event when it is being generated, so that the business analyst has the pre-processed data at his/her disposal when starting the analysis. To this end, we define a notion of intermediate structure between the underlying data and the layer where the actual mining is performed. This intermediate structure is kept in a persistent storage and is kept live under updates. Using a state of the art process mining technique, we show the feasibility of our approach. Our work is implemented in the process mining tool ProM using a relational database system as our persistent storage. Experiments are presented on real-life event data to compare the performance of the proposed approach with the state of the art.

    Original languageEnglish
    Title of host publicationBusiness Process Management Workshops
    Subtitle of host publicationBPM 2017 International Workshops, Barcelona, Spain, September 10-11, 2017, Revised Papers
    EditorsE. Teniente, M. Weidlich
    Place of PublicationDordrecht
    PublisherSpringer
    Pages178-190
    Number of pages13
    ISBN (Electronic)978-3-319-74030-0
    ISBN (Print)978-3-319-74029-4
    DOIs
    Publication statusPublished - 2018
    Event15th International Conference on Business Process Management (BPM 2017) - Barcelona, Spain
    Duration: 10 Sep 201715 Sep 2017
    Conference number: 15
    https://bpm2017.cs.upc.edu/

    Publication series

    NameLecture Notes in Business Information Processing
    Volume308
    ISSN (Print)1865-1348

    Conference

    Conference15th International Conference on Business Process Management (BPM 2017)
    Abbreviated titleBPM 2017
    CountrySpain
    CityBarcelona
    Period10/09/1715/09/17
    Internet address

    Keywords

    • Incremental process discovery
    • Live event data
    • Recurrent process mining
    • Live event data Incremental process discovery

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