An experimental evaluation of passage-based process discovery

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

5 Citations (Scopus)

Abstract

In the area of process mining, the ILP Miner is known for the fact that it always returns a Petri net that perfectly fits a given event log. Like for most process discovery algorithms, its complexity is linear in the size of the event log and exponential in the number of event classes (i.e., distinct activities). As a result, the potential gain by partitioning the event classes is much higher than the potential gain by partitioning the traces in the event log over multiple event logs. This paper proposes to use the so-called passages to split up the event classes over multiple event logs, and shows the results are for seven large real-life event logs and one artificial event log: The use of passages indeed alleviates the complexity, but much hinges on the size of the largest passage detected.
Original languageEnglish
Title of host publicationBusiness Process Management Workshops : BPM 2012 International Workshops, Tallinn, Estonia, September 3, 2012. Revised Papers
EditorsM. La Rosa, P. Soffer
Place of PublicationBerlin
PublisherSpringer
Pages205-210
ISBN (Print)978-3-642-36284-2
DOIs
Publication statusPublished - 2013
Event8th International Workshop on Business Process Intelligence (BPI 2012) - Tallinn, Estonia
Duration: 3 Sep 20123 Sep 2012
Conference number: 8

Publication series

NameLecture Notes in Business Information Processing
Volume132
ISSN (Print)1865-1348

Workshop

Workshop8th International Workshop on Business Process Intelligence (BPI 2012)
Abbreviated titleBPI 2012
Country/TerritoryEstonia
CityTallinn
Period3/09/123/09/12
OtherWorkshop held in conjunction with the 10th International Conference on Business Process Management (BPM 2012)

Fingerprint

Dive into the research topics of 'An experimental evaluation of passage-based process discovery'. Together they form a unique fingerprint.

Cite this