Merging event logs with many to many relationships

Lihi Raichelson, Pnina Soffer

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


Process mining techniques enable the discovery and analysis of business processes, identifying opportunities for improvement. However, processes are often comprised of separately managed procedures that have separate log files, impossible to mine in an integrative manner. A preprocessing step that merges logfiles is quite straightforward when the logs have common case IDs. However, when cases in the different logs have many-to-many relationships among them this is more challenging. In this paper we present an approach for merging event logs which is capable of dealing with all kinds of relationships between logs, one-to-one or many-to-many. The approach matches cases in the logs, using temporal relations and text mining techniques. We have implemented the algorithm and tested it on a comprehensive set of synthetic logs.

Original languageEnglish
Title of host publicationBusiness Process Management Workshops BPM 2014 International Workshops, Revised Papers
EditorsFabiana Fournier, Jan Mendling
PublisherSpringer Verlag
Number of pages12
ISBN (Electronic)9783319158945
StatePublished - 2015
EventInternational Workshops on Business Process Management Workshops, BPM 2014 - Eindhoven, Netherlands
Duration: 7 Sep 20148 Sep 2014

Publication series

NameLecture Notes in Business Information Processing
ISSN (Print)1865-1348


ConferenceInternational Workshops on Business Process Management Workshops, BPM 2014

Bibliographical note

Publisher Copyright:
© Springer International Publishing Switzerland 2015.


  • End-to-end process
  • Merging logfiles
  • Multiple instances
  • Process mining

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Management Information Systems
  • Business and International Management
  • Information Systems
  • Modeling and Simulation
  • Information Systems and Management


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