Efficiently computing alignments: using the extended marking equation

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

2 Citations (Scopus)

Abstract

Conformance checking is considered to be anything where observed behaviour needs to be related to already modelled behaviour. Fundamental to conformance checking are alignments which provide a precise relation between a sequence of activities observed in an event log and a execution sequence of a model. However, computing alignments is a complex task, both in time and memory, especially when models contain large amounts of parallelism. When computing alignments for Petri nets, (Integer) Linear Programming problems based on the marking equation are typically used to guide the search. Solving such problems is the main driver for the time complexity of alignments. In this paper, we adopt existing work in such a way that (a) the extended marking equation is used rather than the marking equation and (b) the number of linear problems that is solved is kept at a minimum. To do so, we exploit fundamental properties of the Petri nets and we show that we are able to compute optimal alignments for models for which this was previously infeasible. Furthermore, using a large collection of benchmark models, we empirically show that we improve on the state-of-the-art in terms of time and memory complexity.

Original languageEnglish
Title of host publicationBusiness Process Management - 16th International Conference, BPM 2018, Proceedings
EditorsMarco Montali, Ingo Weber, Mathias Weske, Jan vom Brocke
Place of PublicationCham
PublisherSpringer
Pages197-214
Number of pages18
ISBN (Electronic)978-3-319-98648-7
ISBN (Print)978-3-319-98647-0
DOIs
Publication statusPublished - 1 Jan 2018
Event16th International Conference on Business Process Management, BPM 2018 - Sydney, Australia
Duration: 9 Sep 201814 Sep 2018

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11080 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference16th International Conference on Business Process Management, BPM 2018
CountryAustralia
CitySydney
Period9/09/1814/09/18

Fingerprint

Alignment
Computing
Petri nets
Petri Nets
Data storage equipment
Integer Linear Programming
Model
Linear programming
Time Complexity
Parallelism
Driver
Benchmark

Keywords

  • Alignments
  • Conformance checking
  • Process Mining

Cite this

van Dongen, B. F. (2018). Efficiently computing alignments: using the extended marking equation. In M. Montali, I. Weber, M. Weske, & J. vom Brocke (Eds.), Business Process Management - 16th International Conference, BPM 2018, Proceedings (pp. 197-214). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11080 LNCS). Cham: Springer. https://doi.org/10.1007/978-3-319-98648-7_12
van Dongen, Boudewijn F. / Efficiently computing alignments : using the extended marking equation. Business Process Management - 16th International Conference, BPM 2018, Proceedings. editor / Marco Montali ; Ingo Weber ; Mathias Weske ; Jan vom Brocke. Cham : Springer, 2018. pp. 197-214 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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van Dongen, BF 2018, Efficiently computing alignments: using the extended marking equation. in M Montali, I Weber, M Weske & J vom Brocke (eds), Business Process Management - 16th International Conference, BPM 2018, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 11080 LNCS, Springer, Cham, pp. 197-214, 16th International Conference on Business Process Management, BPM 2018, Sydney, Australia, 9/09/18. https://doi.org/10.1007/978-3-319-98648-7_12

Efficiently computing alignments : using the extended marking equation. / van Dongen, Boudewijn F.

Business Process Management - 16th International Conference, BPM 2018, Proceedings. ed. / Marco Montali; Ingo Weber; Mathias Weske; Jan vom Brocke. Cham : Springer, 2018. p. 197-214 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11080 LNCS).

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

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van Dongen BF. Efficiently computing alignments: using the extended marking equation. In Montali M, Weber I, Weske M, vom Brocke J, editors, Business Process Management - 16th International Conference, BPM 2018, Proceedings. Cham: Springer. 2018. p. 197-214. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-319-98648-7_12