Detection and interactive repair of event ordering imperfection in process logs

Prabhakar M. Dixit, Suriadi Suriadi, Robert Andrews, Moe T. Wynn, Arthur H.M. ter Hofstede, Joos C.A.M. Buijs, Wil M.P. van der Aalst

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

13 Citations (Scopus)

Abstract

Many forms of data analysis require timestamp information to order the occurrences of events. The process mining discipline uses historical records of process executions, called event logs, to derive insights into business process behaviours and performance. Events in event logs must be ordered, typically achieved using timestamps. The importance of timestamp information means that it needs to be of high quality. To the best of our knowledge, no (semi-)automated support exists for detecting and repairing ordering-related imperfection issues in event logs. We describe a set of timestamp-based indicators for detecting event ordering imperfection issues in a log and our approach to repairing identified issues using domain knowledge. Lastly, we evaluate our approach implemented in the open-source process mining framework, ProM, using two publicly available logs.

Original languageEnglish
Title of host publicationAdvanced Information Systems Engineering - 30th International Conference, CAiSE 2018, Proceedings
PublisherSpringer
Pages274-290
Number of pages17
ISBN (Print)9783319915623
DOIs
Publication statusPublished - 1 Jan 2018
Event30th International Conference on Advanced Information Systems Engineering (CAiSE 2018) - Tallinn, Estonia
Duration: 11 Jun 201815 Jun 2018
Conference number: 30
https://caise2018.ut.ee/

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10816 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference30th International Conference on Advanced Information Systems Engineering (CAiSE 2018)
Abbreviated titleCAiSE 2018
CountryEstonia
CityTallinn
Period11/06/1815/06/18
Internet address

Keywords

  • Data quality
  • Event log imperfection
  • Event ordering

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