Indulpet miner: combining discovery algorithms

Sander J.J. Leemans, Niek Tax, Arthur H.M. ter Hofstede

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

    3 Citations (Scopus)

    Abstract

    In this work, we explore an approach to process discovery that is based on combining several existing process discovery algorithms. We focus on algorithms that generate process models in the process tree notation, which are sound by design. The main components of our proposed process discovery approach are the Inductive Miner, the Evolutionary Tree Miner, the Local Process Model Miner and a new bottom-up recursive technique. We conjecture that the combination of these process discovery algorithms can mitigate some of the weaknesses of the individual algorithms. In cases where the Inductive Miner results in overgeneralizing process models, the Evolutionary Tree Miner can often mine much more precise models. At the other hand, while the Evolutionary Tree Miner is computationally expensive, running it only on parts of the log that the Inductive Miner is not able to represent with a precise model fragment can considerably limit the search space size of the Evolutionary Tree Miner. Local Process Models and bottom-up recursion aid the Evolutionary Tree Miner further by instantiating it with frequent process model fragments. We evaluate our approaches on a collection of real-life event logs and find that it does combine the advantages of the miners and in some cases surpasses other discovery techniques.

    Original languageEnglish
    Title of host publicationOn the Move to Meaningful Internet Systems. OTM 2018 Conferences - Confederated International Conferences
    Subtitle of host publicationCoopIS, C and TC, and ODBASE 2018, Proceedings
    EditorsHenderik A. Proper, Robert Meersman, Claudio Agostino Ardagna, Hervé Panetto, Christophe Debruyne, Dumitru Roman
    Place of PublicationCham
    PublisherSpringer
    Pages97-115
    Number of pages19
    ISBN (Electronic)978-3-030-02610-3
    ISBN (Print)978-3-030-02609-7
    DOIs
    Publication statusPublished - 1 Jan 2018
    EventConfederated International Conferences: Cooperative Information Systems, CoopIS 2018, Ontologies, Databases, and Applications of Semantics, ODBASE 2018, and Cloud and Trusted Computing, C and TC, held as part of OTM 2018 - Valletta, Malta
    Duration: 22 Oct 201826 Oct 2018

    Publication series

    NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
    Volume11229 LNCS
    ISSN (Print)0302-9743
    ISSN (Electronic)1611-3349

    Conference

    ConferenceConfederated International Conferences: Cooperative Information Systems, CoopIS 2018, Ontologies, Databases, and Applications of Semantics, ODBASE 2018, and Cloud and Trusted Computing, C and TC, held as part of OTM 2018
    CountryMalta
    CityValletta
    Period22/10/1826/10/18

    Keywords

    • Boosting
    • Bottom-up recursion
    • Process discovery
    • Process mining
    • Process trees

    Fingerprint Dive into the research topics of 'Indulpet miner: combining discovery algorithms'. Together they form a unique fingerprint.

    Cite this