License: Creative Commons Attribution 3.0 Unported license (CC BY 3.0)
When quoting this document, please refer to the following
DOI: 10.4230/DagRep.3.11.154
URN: urn:nbn:de:0030-drops-44417
URL: http://dagstuhl.sunsite.rwth-aachen.de/volltexte/2014/4441/
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Accorsi, Rafael ; Damiani, Ernesto ; van der Aalst, Wil
Weitere Beteiligte (Hrsg. etc.): Rafael Accorsi and Ernesto Damiani and Wil van der Aalst

Unleashing Operational Process Mining (Dagstuhl Seminar 13481)

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dagrep_v003_i011_p154_s13481.pdf (2 MB)

Abstract

This report documents the program and the outcomes of Dagstuhl Seminar 13481 "Unleashing Operational Process Mining". Process mining is a young research discipline connecting computational intelligence and data mining on the one hand and process modeling and analysis on the other hand. The goal of process mining is to discover, monitor, diagnose and improve real processes by extracting knowledge from event logs readily available in today's information systems. Process mining bridges the gap between data mining and business process modeling and analysis. The seminar that took place November 2013 was the first in its kind. About 50 process mining experts joined forces to discuss the main process mining challenges and present cutting edge results. This report aims to describe the presentations, discussions, and findings.

BibTeX - Entry

@Article{accorsi_et_al:DR:2014:4441,
  author =	{Rafael Accorsi and Ernesto Damiani and Wil van der Aalst},
  title =	{{Unleashing Operational Process Mining (Dagstuhl Seminar 13481)}},
  pages =	{154--192},
  journal =	{Dagstuhl Reports},
  ISSN =	{2192-5283},
  year =	{2014},
  volume =	{3},
  number =	{11},
  editor =	{Rafael Accorsi and Ernesto Damiani and Wil van der Aalst},
  publisher =	{Schloss Dagstuhl--Leibniz-Zentrum fuer Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{http://drops.dagstuhl.de/opus/volltexte/2014/4441},
  URN =		{urn:nbn:de:0030-drops-44417},
  doi =		{10.4230/DagRep.3.11.154},
  annote =	{Keywords: Process mining, Big data, Conformance checking}
}

Keywords: Process mining, Big data, Conformance checking
Collection: Dagstuhl Reports, Volume 3, Issue 11
Issue Date: 2014
Date of publication: 21.03.2014

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