Improving Simplicity by Discovering Nested Groups in Declarative Models

Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

Standard

Improving Simplicity by Discovering Nested Groups in Declarative Models. / Cosma, Vlad Paul; Christfort, Axel Kjeld Fjelrad; Hildebrandt, Thomas T.; Lu, Xixi; Reijers, Hajo A.; Slaats, Tijs.

Advanced Information Systems Engineering - 36th International Conference, CAiSE 2024, Proceedings. ed. / Giancarlo Guizzardi; Flavia Santoro; Haralambos Mouratidis; Pnina Soffer. Springer, 2024. p. 440-455 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol. 14663 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

Harvard

Cosma, VP, Christfort, AKF, Hildebrandt, TT, Lu, X, Reijers, HA & Slaats, T 2024, Improving Simplicity by Discovering Nested Groups in Declarative Models. in G Guizzardi, F Santoro, H Mouratidis & P Soffer (eds), Advanced Information Systems Engineering - 36th International Conference, CAiSE 2024, Proceedings. Springer, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 14663 LNCS, pp. 440-455, 36th International Conference on Advanced Information Systems Engineering, CAiSE 2024, Limassol, Cyprus, 03/06/2024. https://doi.org/10.1007/978-3-031-61057-8_26

APA

Cosma, V. P., Christfort, A. K. F., Hildebrandt, T. T., Lu, X., Reijers, H. A., & Slaats, T. (2024). Improving Simplicity by Discovering Nested Groups in Declarative Models. In G. Guizzardi, F. Santoro, H. Mouratidis, & P. Soffer (Eds.), Advanced Information Systems Engineering - 36th International Conference, CAiSE 2024, Proceedings (pp. 440-455). Springer. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 14663 LNCS https://doi.org/10.1007/978-3-031-61057-8_26

Vancouver

Cosma VP, Christfort AKF, Hildebrandt TT, Lu X, Reijers HA, Slaats T. Improving Simplicity by Discovering Nested Groups in Declarative Models. In Guizzardi G, Santoro F, Mouratidis H, Soffer P, editors, Advanced Information Systems Engineering - 36th International Conference, CAiSE 2024, Proceedings. Springer. 2024. p. 440-455. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol. 14663 LNCS). https://doi.org/10.1007/978-3-031-61057-8_26

Author

Cosma, Vlad Paul ; Christfort, Axel Kjeld Fjelrad ; Hildebrandt, Thomas T. ; Lu, Xixi ; Reijers, Hajo A. ; Slaats, Tijs. / Improving Simplicity by Discovering Nested Groups in Declarative Models. Advanced Information Systems Engineering - 36th International Conference, CAiSE 2024, Proceedings. editor / Giancarlo Guizzardi ; Flavia Santoro ; Haralambos Mouratidis ; Pnina Soffer. Springer, 2024. pp. 440-455 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol. 14663 LNCS).

Bibtex

@inproceedings{cb4d23dde9404a3bac90ccb072ea9f0a,
title = "Improving Simplicity by Discovering Nested Groups in Declarative Models",
abstract = "Discovering simple, understandable and yet accurate process models is a well-known issue for models mined from real-life event logs. In this paper, we consider algorithms for automatically computing nested groups of activities in declarative process languages, concretely Dynamic Condition Response (DCR) Graphs, to reduce complexity while preserving accuracy. The DCR Graphs notation is, on the one hand, supported by the very accurate DisCoveR process mining algorithm, and on the other hand, by mature design and execution tools used in industrial processes and enterprise information management systems. We evaluate our approach by applying the DisCoveR miner to a large benchmark of real-life and synthetic event logs, measuring the size, density, separability, and constraint variability of mined models with and without grouping of activities. In earlier work, these measures have been shown to have a significant effect on the intrinsic cognitive load for users of declarative models, in particular DCR Graphs. We also evaluate the effect of prioritizing in particular the grouping of activities that model mutual exclusive choices. Our evaluation confirms that grouping of activities in general lowers the complexity on 3 of the 4 measures, while prioritizing choices in some cases makes the improvement slightly smaller.",
keywords = "Choices, DCR Graphs, Declarative, Nested Groups, Process Discovery, Simplicity",
author = "Cosma, {Vlad Paul} and Christfort, {Axel Kjeld Fjelrad} and Hildebrandt, {Thomas T.} and Xixi Lu and Reijers, {Hajo A.} and Tijs Slaats",
note = "Publisher Copyright: {\textcopyright} The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.; 36th International Conference on Advanced Information Systems Engineering, CAiSE 2024 ; Conference date: 03-06-2024 Through 07-06-2024",
year = "2024",
doi = "10.1007/978-3-031-61057-8_26",
language = "English",
isbn = "9783031610561",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer",
pages = "440--455",
editor = "Giancarlo Guizzardi and Flavia Santoro and Haralambos Mouratidis and Pnina Soffer",
booktitle = "Advanced Information Systems Engineering - 36th International Conference, CAiSE 2024, Proceedings",
address = "Switzerland",

}

RIS

TY - GEN

T1 - Improving Simplicity by Discovering Nested Groups in Declarative Models

AU - Cosma, Vlad Paul

AU - Christfort, Axel Kjeld Fjelrad

AU - Hildebrandt, Thomas T.

AU - Lu, Xixi

AU - Reijers, Hajo A.

AU - Slaats, Tijs

N1 - Publisher Copyright: © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

PY - 2024

Y1 - 2024

N2 - Discovering simple, understandable and yet accurate process models is a well-known issue for models mined from real-life event logs. In this paper, we consider algorithms for automatically computing nested groups of activities in declarative process languages, concretely Dynamic Condition Response (DCR) Graphs, to reduce complexity while preserving accuracy. The DCR Graphs notation is, on the one hand, supported by the very accurate DisCoveR process mining algorithm, and on the other hand, by mature design and execution tools used in industrial processes and enterprise information management systems. We evaluate our approach by applying the DisCoveR miner to a large benchmark of real-life and synthetic event logs, measuring the size, density, separability, and constraint variability of mined models with and without grouping of activities. In earlier work, these measures have been shown to have a significant effect on the intrinsic cognitive load for users of declarative models, in particular DCR Graphs. We also evaluate the effect of prioritizing in particular the grouping of activities that model mutual exclusive choices. Our evaluation confirms that grouping of activities in general lowers the complexity on 3 of the 4 measures, while prioritizing choices in some cases makes the improvement slightly smaller.

AB - Discovering simple, understandable and yet accurate process models is a well-known issue for models mined from real-life event logs. In this paper, we consider algorithms for automatically computing nested groups of activities in declarative process languages, concretely Dynamic Condition Response (DCR) Graphs, to reduce complexity while preserving accuracy. The DCR Graphs notation is, on the one hand, supported by the very accurate DisCoveR process mining algorithm, and on the other hand, by mature design and execution tools used in industrial processes and enterprise information management systems. We evaluate our approach by applying the DisCoveR miner to a large benchmark of real-life and synthetic event logs, measuring the size, density, separability, and constraint variability of mined models with and without grouping of activities. In earlier work, these measures have been shown to have a significant effect on the intrinsic cognitive load for users of declarative models, in particular DCR Graphs. We also evaluate the effect of prioritizing in particular the grouping of activities that model mutual exclusive choices. Our evaluation confirms that grouping of activities in general lowers the complexity on 3 of the 4 measures, while prioritizing choices in some cases makes the improvement slightly smaller.

KW - Choices

KW - DCR Graphs

KW - Declarative

KW - Nested Groups

KW - Process Discovery

KW - Simplicity

U2 - 10.1007/978-3-031-61057-8_26

DO - 10.1007/978-3-031-61057-8_26

M3 - Article in proceedings

AN - SCOPUS:85196753558

SN - 9783031610561

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 440

EP - 455

BT - Advanced Information Systems Engineering - 36th International Conference, CAiSE 2024, Proceedings

A2 - Guizzardi, Giancarlo

A2 - Santoro, Flavia

A2 - Mouratidis, Haralambos

A2 - Soffer, Pnina

PB - Springer

T2 - 36th International Conference on Advanced Information Systems Engineering, CAiSE 2024

Y2 - 3 June 2024 through 7 June 2024

ER -

ID: 397029243