Discovering more precise process models from event logs by filtering out chaotic activities

Autor: Niek Tax, Natalia Sidorova, Wil M. P. van der Aalst
Přispěvatelé: Process Science
Jazyk: angličtina
Rok vydání: 2019
Předmět:
FOS: Computer and information sciences
Process modeling
Computer Networks and Communications
Business process
Computer science
Computer Science - Artificial Intelligence
Computer Science - Information Theory
Chaotic
Process mining
02 engineering and technology
computer.software_genre
Machine Learning (cs.LG)
Business process management
Business process discovery
Knowledge discovery
Computer Science - Databases
Artificial Intelligence
0202 electrical engineering
electronic engineering
information engineering
Information systems
Business process intelligence
business.industry
Event (computing)
Information Theory (cs.IT)
Databases (cs.DB)
Filter (signal processing)
Computer Science - Learning
Artificial Intelligence (cs.AI)
Hardware and Architecture
020201 artificial intelligence & image processing
Data mining
ddc:004
business
computer
Software
Zdroj: Journal of Intelligent Information Systems, 52(1), 107-139. Springer
Journal of intelligent information systems : JIIS 52(1), 107-139 (2019). doi:10.1007/s10844-018-0507-6
ISSN: 1573-7675
0925-9902
DOI: 10.1007/s10844-018-0507-6
Popis: Journal of intelligent information systems : JIIS 52(1), 107-139 (2019). doi:10.1007/s10844-018-0507-6
Published by Springer Science + Business Media B.V, Dordrecht
Databáze: OpenAIRE
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