Improving Declarative Process Mining with a Priori Noise Filtering

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

In this paper, we report the results of an exploratory study into the efficacy of noise filtering in improving the accuracy of declarative process mining. We apply the double-granularity mixed-dependency filtering algorithm as introduced by [9], to the DisCoveR declarative miner [1], and parameter optimise it to only perform coarse-grained filtering. However, while noise filtering appears promising on the surface, one might worry that the outlier behaviour allowed by declarative models may be wrongly classified as noise and removed. To test the efficacy of noise filtering from both perspectives, we applied DisCoveR with noise filtering to two data sets: the process log collection used in the PDC2020 process discovery contest, emulating “real-world” scenarios; and a synthetic set of logs known to exhibit (non-noise) outlier behaviour. We find that on the contest data sets, noise filtering significantly increases accuracy (on average 23% points), obtaining exploratory evidence that noise filtering may improve declarative miner performance; on the synthetic logs we showcase examples where noise is filtered, while outlier behaviour remains untouched.

Original languageEnglish
Title of host publicationBusiness Process Management Workshops - BPM 2022 International Workshops, Revised Selected Papers
EditorsCristina Cabanillas, Niels Frederik Garmann-Johnsen, Agnes Koschmider
PublisherSpringer
Publication date2023
Pages286-297
ISBN (Print)9783031253829
DOIs
Publication statusPublished - 2023
EventWorkshops on AI4BPM, BP-Meet-IoT, BPI, BPM and RD, BPMS2, BPO, DEC2H, and NLP4BPM 2022, co-located with the 20th International Conference on Business Process Management, BPM 2022 - Münster, Germany
Duration: 11 Sep 202216 Sep 2022

Conference

ConferenceWorkshops on AI4BPM, BP-Meet-IoT, BPI, BPM and RD, BPMS2, BPO, DEC2H, and NLP4BPM 2022, co-located with the 20th International Conference on Business Process Management, BPM 2022
LandGermany
ByMünster
Periode11/09/202216/09/2022
SeriesLecture Notes in Business Information Processing
Volume460 LNBIP
ISSN1865-1348

Bibliographical note

Publisher Copyright:
© 2023, Springer Nature Switzerland AG.

    Research areas

  • DCR Graphs, Declarative process models, Noise filtering, Process discovery

ID: 343224343