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Utilizing domain knowledge in data-driven process discovery : A literature review

; ;

In
Computers in industry 137, Seiten/Artikel-Nr.:103612

ImpressumAmsterdam [u.a.] : Elsevier Science

Umfang[1]-19

ISSN0166-3615

Online
DOI: 10.1016/j.compind.2022.103612

DOI: 10.18154/RWTH-2022-02465
URL: https://publications.rwth-aachen.de/record/842446/files/842446.pdf

Einrichtungen

  1. Lehrstuhl für Process and Data Science (122510)
  2. Fachgruppe Informatik (120000)


Thematische Einordnung (Klassifikation)
DDC: 070

OpenAccess:
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Dokumenttyp
Journal Article (Review Article)

Format
online, print

Sprache
English

Anmerkung
Peer reviewed article

Externe Identnummern
SCOPUS: SCOPUS:2-s2.0-85124241347
WOS Core Collection: WOS:000754186600001

Interne Identnummern
RWTH-2022-02465
Datensatz-ID: 842446

Beteiligte Länder
Germany

Lizenzstatus der Zeitschrift

 GO

Medline ; Creative Commons Attribution CC BY 4.0 ; OpenAccess ; Clarivate Analytics Master Journal List ; Current Contents - Engineering, Computing and Technology ; Essential Science Indicators ; IF < 5 ; JCR ; SCOPUS ; Science Citation Index Expanded ; Web of Science Core Collection
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Publication server / Open Access
Faculty of Computer Science (Fac.9)
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122510
120000
 Record created 2022-03-07, last modified 2022-07-28
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