Multi-instance mining: discovering synchronisation in artifact-centric processes

Maikel L. van Eck; Natalia Sidorova; Wil M.P. van der Aalst

doi:10.1007/978-3-030-11641-5_2

Multi-instance mining: discovering synchronisation in artifact-centric processes

Maikel L. van Eck, Natalia Sidorova, Wil M.P. van der Aalst

Process Analytics

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

7 Citations (Scopus)

1 Downloads (Pure)

Abstract

In complex systems one can often identify various entities or artifacts. The lifecycles of these artifacts and the loosely coupled interactions between them define the system behavior. The analysis of such artifact system behavior with traditional process discovery techniques is often problematic due to the existence of many-to-many relationships between artifacts, resulting in models that are difficult to understand and statistics that are inaccurate. The aim of this work is to address these issues and enable the calculation of statistics regarding the synchronisation of behaviour between artifact instances. By using a Petri net formalisation with step sequence execution semantics to support true concurrency, we create state-based artifact lifecycle models that support many-to-many relations between artifacts. The approach has been implemented as an interactive visualisation in ProM and evaluated using real-life public data.

Original language	English
Title of host publication	Business Process Management Workshops - BPM 2018 International Workshops, Revised Papers
Editors	Florian Daniel, Quan Z. Sheng, Hamid Motahari
Place of Publication	Cham
Publisher	Springer
Pages	18-30
Number of pages	13
ISBN (Electronic)	978-3-030-11641-5
ISBN (Print)	978-3-030-11640-8
DOIs	https://doi.org/10.1007/978-3-030-11641-5_2
Publication status	Published - 1 Jan 2019
Event	16th International Conference on Business Process Management (BPM 2018) - Sydney, Australia Duration: 9 Sept 2018 → 14 Sept 2018 Conference number: 16 http://ceur-ws.org/Vol-2196/

Publication series

Name	Lecture Notes in Business Information Processing
Volume	342
ISSN (Print)	1865-1348

Conference

Conference	16th International Conference on Business Process Management (BPM 2018)
Abbreviated title	BPM 2018
Country/Territory	Australia
City	Sydney
Period	9/09/18 → 14/09/18
Other	Dissertation Award, Demonstration, and Industrial Track at BPM
Internet address	http://ceur-ws.org/Vol-2196/

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10.1007/978-3-030-11641-5_2

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van Eck, M. L., Sidorova, N., & van der Aalst, W. M. P. (2019). Multi-instance mining: discovering synchronisation in artifact-centric processes. In F. Daniel, Q. Z. Sheng, & H. Motahari (Eds.), Business Process Management Workshops - BPM 2018 International Workshops, Revised Papers (pp. 18-30). (Lecture Notes in Business Information Processing; Vol. 342). Springer. https://doi.org/10.1007/978-3-030-11641-5_2

van Eck, Maikel L. ; Sidorova, Natalia ; van der Aalst, Wil M.P. / Multi-instance mining : discovering synchronisation in artifact-centric processes. Business Process Management Workshops - BPM 2018 International Workshops, Revised Papers. editor / Florian Daniel ; Quan Z. Sheng ; Hamid Motahari. Cham : Springer, 2019. pp. 18-30 (Lecture Notes in Business Information Processing).

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abstract = "In complex systems one can often identify various entities or artifacts. The lifecycles of these artifacts and the loosely coupled interactions between them define the system behavior. The analysis of such artifact system behavior with traditional process discovery techniques is often problematic due to the existence of many-to-many relationships between artifacts, resulting in models that are difficult to understand and statistics that are inaccurate. The aim of this work is to address these issues and enable the calculation of statistics regarding the synchronisation of behaviour between artifact instances. By using a Petri net formalisation with step sequence execution semantics to support true concurrency, we create state-based artifact lifecycle models that support many-to-many relations between artifacts. The approach has been implemented as an interactive visualisation in ProM and evaluated using real-life public data.",

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van Eck, ML, Sidorova, N & van der Aalst, WMP 2019, Multi-instance mining: discovering synchronisation in artifact-centric processes. in F Daniel, QZ Sheng & H Motahari (eds), Business Process Management Workshops - BPM 2018 International Workshops, Revised Papers. Lecture Notes in Business Information Processing, vol. 342, Springer, Cham, pp. 18-30, 16th International Conference on Business Process Management (BPM 2018), Sydney, Australia, 9/09/18. https://doi.org/10.1007/978-3-030-11641-5_2

Multi-instance mining: discovering synchronisation in artifact-centric processes. / van Eck, Maikel L.; Sidorova, Natalia; van der Aalst, Wil M.P.
Business Process Management Workshops - BPM 2018 International Workshops, Revised Papers. ed. / Florian Daniel; Quan Z. Sheng; Hamid Motahari. Cham: Springer, 2019. p. 18-30 (Lecture Notes in Business Information Processing; Vol. 342).

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

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T1 - Multi-instance mining

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AU - Sidorova, Natalia

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N1 - Conference code: 16

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N2 - In complex systems one can often identify various entities or artifacts. The lifecycles of these artifacts and the loosely coupled interactions between them define the system behavior. The analysis of such artifact system behavior with traditional process discovery techniques is often problematic due to the existence of many-to-many relationships between artifacts, resulting in models that are difficult to understand and statistics that are inaccurate. The aim of this work is to address these issues and enable the calculation of statistics regarding the synchronisation of behaviour between artifact instances. By using a Petri net formalisation with step sequence execution semantics to support true concurrency, we create state-based artifact lifecycle models that support many-to-many relations between artifacts. The approach has been implemented as an interactive visualisation in ProM and evaluated using real-life public data.

AB - In complex systems one can often identify various entities or artifacts. The lifecycles of these artifacts and the loosely coupled interactions between them define the system behavior. The analysis of such artifact system behavior with traditional process discovery techniques is often problematic due to the existence of many-to-many relationships between artifacts, resulting in models that are difficult to understand and statistics that are inaccurate. The aim of this work is to address these issues and enable the calculation of statistics regarding the synchronisation of behaviour between artifact instances. By using a Petri net formalisation with step sequence execution semantics to support true concurrency, we create state-based artifact lifecycle models that support many-to-many relations between artifacts. The approach has been implemented as an interactive visualisation in ProM and evaluated using real-life public data.

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van Eck ML, Sidorova N, van der Aalst WMP. Multi-instance mining: discovering synchronisation in artifact-centric processes. In Daniel F, Sheng QZ, Motahari H, editors, Business Process Management Workshops - BPM 2018 International Workshops, Revised Papers. Cham: Springer. 2019. p. 18-30. (Lecture Notes in Business Information Processing). doi: 10.1007/978-3-030-11641-5_2

Multi-instance mining: discovering synchronisation in artifact-centric processes

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