Mining Hybrid Business Process Models: A Quest for Better Precision

Dennis M. M. Schunselaar, Tijs Slaats, Fabrizio M. Maggi, Hajo A. Reijers, Wil M. P. Van Der Aalst

    6 Citationer (Scopus)

    Abstract

    In this paper, we present a technique for the discovery of hybrid process models that combine imperative and declarative constructs. In particular, we first employ the popular Inductive Miner to generate a fully imperative model from a log. Like most imperative miners, the Inductive Miner tends to return so-called flower models for the less structured parts of the process. These parts are often imprecise. To counter these imprecise parts, we replace them with declarative models to increase the precision since declarative models are good at specifying which behavior is disallowed. The approach has been implemented in ProM and tested on several synthetic and real-life event logs. Our experiments show that hybrid models can be found to be more precise without overfitting the data.

    OriginalsprogEngelsk
    TitelBusiness Information Systems : 21st International Conference, BIS 2018 Berlin, Germany, July 18–20, 2018 Proceedings
    RedaktørerWitold Abramowicz, Adrian Paschke
    Antal sider16
    ForlagSpringer
    Publikationsdato2018
    Sider190-205
    Kapitel14
    ISBN (Trykt)978-3-319-93930-8
    ISBN (Elektronisk)978-3-319-93931-5
    DOI
    StatusUdgivet - 2018
    Begivenhed21th International Conference on Business Information Systems - Berlin, Tyskland
    Varighed: 18 jul. 201820 jul. 2018

    Konference

    Konference21th International Conference on Business Information Systems
    Land/OmrådeTyskland
    ByBerlin
    Periode18/07/201820/07/2018
    NavnLecture Notes in Business Information Processing
    Vol/bind320
    ISSN1865-1348

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