DisCoveR: Process Mining for Knowledge-Intensive Processes with DCR Graphs

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DisCoveR : Process Mining for Knowledge-Intensive Processes with DCR Graphs. / Slaats, Tijs.

In: CEUR Workshop Proceedings, Vol. 3424, 2023.

Research output: Contribution to journalConference articleResearchpeer-review

Harvard

Slaats, T 2023, 'DisCoveR: Process Mining for Knowledge-Intensive Processes with DCR Graphs', CEUR Workshop Proceedings, vol. 3424.

APA

Slaats, T. (2023). DisCoveR: Process Mining for Knowledge-Intensive Processes with DCR Graphs. CEUR Workshop Proceedings, 3424.

Vancouver

Slaats T. DisCoveR: Process Mining for Knowledge-Intensive Processes with DCR Graphs. CEUR Workshop Proceedings. 2023;3424.

Author

Slaats, Tijs. / DisCoveR : Process Mining for Knowledge-Intensive Processes with DCR Graphs. In: CEUR Workshop Proceedings. 2023 ; Vol. 3424.

Bibtex

@inproceedings{8017069b7cb94747a67646643e824657,
title = "DisCoveR: Process Mining for Knowledge-Intensive Processes with DCR Graphs",
abstract = "Constraint-based notations aim to model processes by capturing their underlying rules instead of a limited number of potential process flows, leaving maximum flexibility for the actor to choose the best-suited order of execution for a particular process instance. Dynamic Condition Response (DCR) graphs are a constraint-based notation that has seen significant industrial adoption. In recent years there have been made significant inroads into the development of process mining algorithms and techniques for DCR Graphs. In this paper, accompanying the keynote of the same name delivered at the workshop Algorithms & Theories for the Analysis of Event Data, we discuss some of these recent advances in process mining with DCR Graphs and conclude by identifying a number of open challenges for DCR-based process mining.",
keywords = "DCR Graphs, Process Mining",
author = "Tijs Slaats",
note = "Publisher Copyright: {\textcopyright} 2022 Copyright for this paper by its authors.; 2023 Joint of the Workshop on Algorithms and Theories for the Analysis of Event Data and the International Workshop on Petri Nets for Twin Transition, ATAED and PN4TT 2023 ; Conference date: 25-06-2023 Through 30-06-2023",
year = "2023",
language = "English",
volume = "3424",
journal = "CEUR Workshop Proceedings",
issn = "1613-0073",
publisher = "ceur workshop proceedings",

}

RIS

TY - GEN

T1 - DisCoveR

T2 - 2023 Joint of the Workshop on Algorithms and Theories for the Analysis of Event Data and the International Workshop on Petri Nets for Twin Transition, ATAED and PN4TT 2023

AU - Slaats, Tijs

N1 - Publisher Copyright: © 2022 Copyright for this paper by its authors.

PY - 2023

Y1 - 2023

N2 - Constraint-based notations aim to model processes by capturing their underlying rules instead of a limited number of potential process flows, leaving maximum flexibility for the actor to choose the best-suited order of execution for a particular process instance. Dynamic Condition Response (DCR) graphs are a constraint-based notation that has seen significant industrial adoption. In recent years there have been made significant inroads into the development of process mining algorithms and techniques for DCR Graphs. In this paper, accompanying the keynote of the same name delivered at the workshop Algorithms & Theories for the Analysis of Event Data, we discuss some of these recent advances in process mining with DCR Graphs and conclude by identifying a number of open challenges for DCR-based process mining.

AB - Constraint-based notations aim to model processes by capturing their underlying rules instead of a limited number of potential process flows, leaving maximum flexibility for the actor to choose the best-suited order of execution for a particular process instance. Dynamic Condition Response (DCR) graphs are a constraint-based notation that has seen significant industrial adoption. In recent years there have been made significant inroads into the development of process mining algorithms and techniques for DCR Graphs. In this paper, accompanying the keynote of the same name delivered at the workshop Algorithms & Theories for the Analysis of Event Data, we discuss some of these recent advances in process mining with DCR Graphs and conclude by identifying a number of open challenges for DCR-based process mining.

KW - DCR Graphs

KW - Process Mining

UR - http://www.scopus.com/inward/record.url?scp=85163893275&partnerID=8YFLogxK

M3 - Conference article

AN - SCOPUS:85163893275

VL - 3424

JO - CEUR Workshop Proceedings

JF - CEUR Workshop Proceedings

SN - 1613-0073

Y2 - 25 June 2023 through 30 June 2023

ER -

ID: 360260985