Discovering block-structured process models from event logs containing infrequent behaviour

S.J.J. Leemans; D. Fahland; W.M.P. Aalst, van der

doi:10.1007/978-3-319-06257-0_6

Discovering block-structured process models from event logs containing infrequent behaviour

S.J.J. Leemans
, D. Fahland
, W.M.P. Aalst, van der

Process Analytics

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

368 Citations (Scopus)

1 Downloads (Pure)

Abstract

Given an event log describing observed behaviour, process discovery aims to find a process model that ‘best’ describes this behaviour. A large variety of process discovery algorithms has been proposed. However, no existing algorithm returns a sound model in all cases (free of deadlocks and other anomalies), handles infrequent behaviour well and finishes quickly. We present a technique able to cope with infrequent behaviour and large event logs, while ensuring soundness. The technique has been implemented in ProM and we compare the technique with existing approaches in terms of quality and performance. Keywords: Process mining; Process discovery; Block-structured process models; Soundness; Fitness; Precision; Generalisation

Original language	English
Title of host publication	Business Process Management Workshops : BPM 2013 International Workshops, Beijing, China, August 26, 2013, Revised Papers
Editors	N. Lohmann, M. Song, P. Wohed
Place of Publication	Berlin
Publisher	Springer
Pages	66-78
ISBN (Print)	978-3-319-06256-3
DOIs	https://doi.org/10.1007/978-3-319-06257-0_6
Publication status	Published - 2014
Event	9th International Workshop on Business Process Intelligence (BPI 2013) - Beijing, China Duration: 26 Aug 2013 → 26 Aug 2013 Conference number: 9

Publication series

Name	Lecture Notes in Business Information Processing
Volume	171
ISSN (Print)	1865-1348

Workshop

Workshop	9th International Workshop on Business Process Intelligence (BPI 2013)
Abbreviated title	BPI 2013
Country/Territory	China
City	Beijing
Period	26/08/13 → 26/08/13
Other	Workshop held in conjunction with the 11th International Conference on Business Process Management (BPM 2013)

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10.1007/978-3-319-06257-0_6

Cite this

Leemans, S. J. J., Fahland, D., & Aalst, van der, W. M. P. (2014). Discovering block-structured process models from event logs containing infrequent behaviour. In N. Lohmann, M. Song, & P. Wohed (Eds.), Business Process Management Workshops : BPM 2013 International Workshops, Beijing, China, August 26, 2013, Revised Papers (pp. 66-78). (Lecture Notes in Business Information Processing; Vol. 171). Springer. https://doi.org/10.1007/978-3-319-06257-0_6

Leemans, S.J.J. ; Fahland, D. ; Aalst, van der, W.M.P. / Discovering block-structured process models from event logs containing infrequent behaviour. Business Process Management Workshops : BPM 2013 International Workshops, Beijing, China, August 26, 2013, Revised Papers. editor / N. Lohmann ; M. Song ; P. Wohed. Berlin : Springer, 2014. pp. 66-78 (Lecture Notes in Business Information Processing).

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title = "Discovering block-structured process models from event logs containing infrequent behaviour",

abstract = "Given an event log describing observed behaviour, process discovery aims to find a process model that {\textquoteleft}best{\textquoteright} describes this behaviour. A large variety of process discovery algorithms has been proposed. However, no existing algorithm returns a sound model in all cases (free of deadlocks and other anomalies), handles infrequent behaviour well and finishes quickly. We present a technique able to cope with infrequent behaviour and large event logs, while ensuring soundness. The technique has been implemented in ProM and we compare the technique with existing approaches in terms of quality and performance. Keywords: Process mining; Process discovery; Block-structured process models; Soundness; Fitness; Precision; Generalisation",

author = "S.J.J. Leemans and D. Fahland and \{Aalst, van der\}, W.M.P.",

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editor = "N. Lohmann and M. Song and P. Wohed",

booktitle = "Business Process Management Workshops : BPM 2013 International Workshops, Beijing, China, August 26, 2013, Revised Papers",

address = "Germany",

note = "9th International Workshop on Business Process Intelligence (BPI 2013), BPI 2013 ; Conference date: 26-08-2013 Through 26-08-2013",

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Leemans, SJJ, Fahland, D & Aalst, van der, WMP 2014, Discovering block-structured process models from event logs containing infrequent behaviour. in N Lohmann, M Song & P Wohed (eds), Business Process Management Workshops : BPM 2013 International Workshops, Beijing, China, August 26, 2013, Revised Papers. Lecture Notes in Business Information Processing, vol. 171, Springer, Berlin, pp. 66-78, 9th International Workshop on Business Process Intelligence (BPI 2013), Beijing, China, 26/08/13. https://doi.org/10.1007/978-3-319-06257-0_6

Discovering block-structured process models from event logs containing infrequent behaviour. / Leemans, S.J.J.; Fahland, D.; Aalst, van der, W.M.P.
Business Process Management Workshops : BPM 2013 International Workshops, Beijing, China, August 26, 2013, Revised Papers. ed. / N. Lohmann; M. Song; P. Wohed. Berlin: Springer, 2014. p. 66-78 (Lecture Notes in Business Information Processing; Vol. 171).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

TY - GEN

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N2 - Given an event log describing observed behaviour, process discovery aims to find a process model that ‘best’ describes this behaviour. A large variety of process discovery algorithms has been proposed. However, no existing algorithm returns a sound model in all cases (free of deadlocks and other anomalies), handles infrequent behaviour well and finishes quickly. We present a technique able to cope with infrequent behaviour and large event logs, while ensuring soundness. The technique has been implemented in ProM and we compare the technique with existing approaches in terms of quality and performance. Keywords: Process mining; Process discovery; Block-structured process models; Soundness; Fitness; Precision; Generalisation

AB - Given an event log describing observed behaviour, process discovery aims to find a process model that ‘best’ describes this behaviour. A large variety of process discovery algorithms has been proposed. However, no existing algorithm returns a sound model in all cases (free of deadlocks and other anomalies), handles infrequent behaviour well and finishes quickly. We present a technique able to cope with infrequent behaviour and large event logs, while ensuring soundness. The technique has been implemented in ProM and we compare the technique with existing approaches in terms of quality and performance. Keywords: Process mining; Process discovery; Block-structured process models; Soundness; Fitness; Precision; Generalisation

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Leemans SJJ, Fahland D, Aalst, van der WMP. Discovering block-structured process models from event logs containing infrequent behaviour. In Lohmann N, Song M, Wohed P, editors, Business Process Management Workshops : BPM 2013 International Workshops, Beijing, China, August 26, 2013, Revised Papers. Berlin: Springer. 2014. p. 66-78. (Lecture Notes in Business Information Processing). doi: 10.1007/978-3-319-06257-0_6

Discovering block-structured process models from event logs containing infrequent behaviour

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