Discovering social networks instantly: Moving process mining computations to the database and data entry time

    Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

    5 Citations (Scopus)
    2 Downloads (Pure)

    Abstract

    Process mining aims to turn event data into insights and actions in order to improve processes. To improve process performance it is crucial to get insights into the way people work and collaborate. In this paper, we focus on discovering social networks from event data.
    To be able to deal with large data sets or with an environment which requires repetitive discoveries during the analysis, and still provide results instantly, we use an approach where most of the computation is moved to the database and things are precomputed at data entry time.
    Differently from traditional process mining where event data is stored in file-based system, we store event data in relational databases. Moreover, the database also has a role as an engine to compute the intermediate structure of social network during insertion data.
    By moving computation both in location (to database) and time (to recording time), the discovery of social networks in a process context becomes truly scalable. The approach has been implemented using the open source process mining toolkit ProM. The experiments reported in this paper demonstrate scalability while providing results instantly.
    Original languageEnglish
    Title of host publicationEnterprise, Business-Process and Information Systems Modeling
    Subtitle of host publication18th International Conference, BPMDS 2017, 22nd International Conference, EMMSAD 2017, Held at CAiSE 2017, Essen, Germany, June 12-13, 2017, Proceedings
    EditorsI. Reinhartz-Berger, J. Gulden, S. Nurcan, W. Guédria, P. Bera
    Place of PublicationDordrecht
    PublisherSpringer
    Pages51-67
    Number of pages17
    ISBN (Electronic)978-3-319-59466-8
    ISBN (Print)9783319594651
    DOIs
    Publication statusPublished - 17 May 2017
    Event18th International Conference on Business Process Modeling, Development and Support, BPMDS 2017 and 22nd International Conference on Evaluation and Modeling Methods for Systems Analysis and Development, EMMSAD 2017 held at Conference on Advanced Information Systems Engineering, CAiSE 2017 - Essen, Germany
    Duration: 12 Jun 201713 Jun 2017

    Publication series

    NameLecture Notes in Business Information Processing
    Volume287
    ISSN (Print)1865-1348

    Conference

    Conference18th International Conference on Business Process Modeling, Development and Support, BPMDS 2017 and 22nd International Conference on Evaluation and Modeling Methods for Systems Analysis and Development, EMMSAD 2017 held at Conference on Advanced Information Systems Engineering, CAiSE 2017
    CountryGermany
    CityEssen
    Period12/06/1713/06/17

    Keywords

    • Process mining
    • Relational database
    • Repetitive discovery
    • Social network

    Fingerprint Dive into the research topics of 'Discovering social networks instantly: Moving process mining computations to the database and data entry time'. Together they form a unique fingerprint.

    Cite this