Mining Hybrid Business Process Models: A Quest for Better Precision

Dennis M. M. Schunselaar; Tijs Slaats; Fabrizio M. Maggi; Hajo A. Reijers; Wil M. P. Van Der Aalst

doi:10.1007/978-3-319-93931-5_14

Mining Hybrid Business Process Models: A Quest for Better Precision

Dennis M. M. Schunselaar, Tijs Slaats, Fabrizio M. Maggi, Hajo A. Reijers, Wil M. P. Van Der Aalst

6 Citationer (Scopus)

Abstract

In this paper, we present a technique for the discovery of hybrid process models that combine imperative and declarative constructs. In particular, we first employ the popular Inductive Miner to generate a fully imperative model from a log. Like most imperative miners, the Inductive Miner tends to return so-called flower models for the less structured parts of the process. These parts are often imprecise. To counter these imprecise parts, we replace them with declarative models to increase the precision since declarative models are good at specifying which behavior is disallowed. The approach has been implemented in ProM and tested on several synthetic and real-life event logs. Our experiments show that hybrid models can be found to be more precise without overfitting the data.

Originalsprog	Engelsk
Titel	Business Information Systems : 21st International Conference, BIS 2018 Berlin, Germany, July 18–20, 2018 Proceedings
Redaktører	Witold Abramowicz, Adrian Paschke
Antal sider	16
Forlag	Springer
Publikationsdato	2018
Sider	190-205
Kapitel	14
ISBN (Trykt)	978-3-319-93930-8
ISBN (Elektronisk)	978-3-319-93931-5
DOI	https://doi.org/10.1007/978-3-319-93931-5_14
Status	Udgivet - 2018
Begivenhed	21th International Conference on Business Information Systems - Berlin, Tyskland Varighed: 18 jul. 2018 → 20 jul. 2018

Konference

Konference	21th International Conference on Business Information Systems
Land/Område	Tyskland
By	Berlin
Periode	18/07/2018 → 20/07/2018

Navn	Lecture Notes in Business Information Processing
Vol/bind	320
ISSN	1865-1348

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10.1007/978-3-319-93931-5_14

Citationsformater

Schunselaar, D. M. M., Slaats, T., Maggi, F. M., Reijers, H. A., & Van Der Aalst, W. M. P. (2018). Mining Hybrid Business Process Models: A Quest for Better Precision. I W. Abramowicz, & A. Paschke (red.), Business Information Systems: 21st International Conference, BIS 2018 Berlin, Germany, July 18–20, 2018 Proceedings (s. 190-205). Springer. https://doi.org/10.1007/978-3-319-93931-5_14

Mining Hybrid Business Process Models: A Quest for Better Precision. / Schunselaar, Dennis M. M.; Slaats, Tijs; Maggi, Fabrizio M. et al.
Business Information Systems: 21st International Conference, BIS 2018 Berlin, Germany, July 18–20, 2018 Proceedings. red. / Witold Abramowicz; Adrian Paschke. Springer, 2018. s. 190-205 (Lecture Notes in Business Information Processing, Bind 320).

Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › peer review

Schunselaar, DMM, Slaats, T, Maggi, FM, Reijers, HA & Van Der Aalst, WMP 2018, Mining Hybrid Business Process Models: A Quest for Better Precision. i W Abramowicz & A Paschke (red), Business Information Systems: 21st International Conference, BIS 2018 Berlin, Germany, July 18–20, 2018 Proceedings. Springer, Lecture Notes in Business Information Processing, bind 320, s. 190-205, 21th International Conference on Business Information Systems, Berlin, Tyskland, 18/07/2018. https://doi.org/10.1007/978-3-319-93931-5_14

Schunselaar DMM, Slaats T, Maggi FM, Reijers HA, Van Der Aalst WMP. Mining Hybrid Business Process Models: A Quest for Better Precision. I Abramowicz W, Paschke A, red., Business Information Systems: 21st International Conference, BIS 2018 Berlin, Germany, July 18–20, 2018 Proceedings. Springer. 2018. s. 190-205. (Lecture Notes in Business Information Processing, Bind 320). doi: 10.1007/978-3-319-93931-5_14

Schunselaar, Dennis M. M. ; Slaats, Tijs ; Maggi, Fabrizio M. et al. / Mining Hybrid Business Process Models : A Quest for Better Precision. Business Information Systems: 21st International Conference, BIS 2018 Berlin, Germany, July 18–20, 2018 Proceedings. red. / Witold Abramowicz ; Adrian Paschke. Springer, 2018. s. 190-205 (Lecture Notes in Business Information Processing, Bind 320).

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abstract = "In this paper, we present a technique for the discovery of hybrid process models that combine imperative and declarative constructs. In particular, we first employ the popular Inductive Miner to generate a fully imperative model from a log. Like most imperative miners, the Inductive Miner tends to return so-called flower models for the less structured parts of the process. These parts are often imprecise. To counter these imprecise parts, we replace them with declarative models to increase the precision since declarative models are good at specifying which behavior is disallowed. The approach has been implemented in ProM and tested on several synthetic and real-life event logs. Our experiments show that hybrid models can be found to be more precise without overfitting the data.",

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Mining Hybrid Business Process Models: A Quest for Better Precision

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