Composite state machine miner: Discovering and exploring multi-perspective processes

Maikel L. Van Eck, Natalia Sidorova, Wil M.P. Van Der Aalst

Onderzoeksoutput: Hoofdstuk in Boek/Rapport/CongresprocedureConferentiebijdrageAcademicpeer review

3 Citaten (Scopus)
110 Downloads (Pure)

Samenvatting

Process mining provides fact-based insights into processes based on behaviour captured in event data. An important aspect of this is the discovery of process models from such data. Traditionally, the focus of process discovery is on learning the ordering of activities. We deviate from this dominating activity view on processes to focus on states and state changes. Specifically, we aim to discover state-based models for processes where different facets, or perspectives, of the process can be identified. In this paper we describe an interactive process discovery tool that can be used to discover and explore state-based models for such multi-perspective processes: the Composite State Machine Miner. It quantifies and visualises the interactions between perspectives to provide additional process insights. This tool has been used to analyse the BPI Challenge 2012 data of a loan application process and product user behaviour data gathered by Philips during the development of a smart baby bottle equipped with various sensors.

Originele taal-2Engels
TitelProceedings of the BPM Demo Track 2016
RedacteurenL. Azevedo, C. Cabanillas
UitgeverijCEUR-WS.org
Pagina's73-77
Aantal pagina's5
StatusGepubliceerd - 2016
Evenement14th International Conference on Business Process Management (BPM 2016) - Rio de Janeiro, Brazilië
Duur: 18 sep. 201622 sep. 2016
Congresnummer: 14
http://bpm2016.uniriotec.br/

Publicatie series

NaamCEUR Workshop Proceedings
Volume1789
ISSN van geprinte versie1613-0073

Congres

Congres14th International Conference on Business Process Management (BPM 2016)
Verkorte titelBPM 2016
Land/RegioBrazilië
StadRio de Janeiro
Periode18/09/1622/09/16
Internet adres

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