Detecting deviating behaviors without models

X. Lu, D. Fahland, F.J.H.M. van den Biggelaar, W.M.P. van der Aalst

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

25 Citations (Scopus)

Abstract

Deviation detection is a set of techniques that identify deviations from normative processes in real process executions. These diagnostics are used to derive recommendations for improving business processes. Existing detection techniques identify deviations either only on the process instance level or rely on a normative process model to locate deviating behavior on the event level. However, when normative models are not available, these techniques detect deviations against a less accurate model discovered from the actual behavior, resulting in incorrect diagnostics. In this paper, we propose a novel approach to detect deviation on the event level by identifying frequent common behavior and uncommon behavior among executed process instances, without discovering any normative model. The approach is implemented in ProM and was evaluated in a controlled setting with artificial logs and real-life logs. We compare our approach to existing approaches to investigate its possibilities and limitations. We show that in some cases, it is possible to detect deviating events without a model as accurately as against a given precise normative model.

Original languageEnglish
Title of host publicationBusiness Process Management Workshops
Subtitle of host publicationBPM 2015, 13th International Workshops, Innsbruck, Austria, August 31 – September 3, 2015, Revised Papers
EditorsM. Reichert, H.A. Reijers
Place of PublicationDordrecht
PublisherSpringer
Pages126-139
Number of pages14
ISBN (Electronic)978-3-319-42887-1
ISBN (Print)978-3-319-42886-4
DOIs
Publication statusPublished - 2016
Event13th International Workshops on Business Process Management Workshops (BPM 2015) - Innsbruck, Austria
Duration: 31 Aug 20153 Sep 2015
Conference number: 13
http://bpm2015.q-e.at/

Publication series

NameLecture Notes in Business Information Processing
Volume256
ISSN (Print)18651348

Conference

Conference13th International Workshops on Business Process Management Workshops (BPM 2015)
Abbreviated titleBPM 2015
Country/TerritoryAustria
CityInnsbruck
Period31/08/153/09/15
OtherBPM Demo Session 2015, BPMD 2015 - co-located with the 13th International Conference on Business Process Management, BPM 2015
Internet address

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