Improving Structure: Logical Sequencing of Mined Process Models

Michael Werner, Marcus Nüttgens

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

Abstract

The increasing availability of digital data offers new opportunities for analyzing business processes. Process aware information systems like Enterprise Resource Planning systems store data in the course of transaction processing. This data can be exploited by using process mining techniques. Process mining algorithms produce process models by analyzing recorded event logs. A fundamental challenge in process mining is the creation of purpose-oriented and useful process models. Process mining algorithms commonly refer to the temporal ordering of events for determining the control flow in reconstructed process models. We show how the logical sequence of events can be used instead of the temporal for reconstructing the control flow in mined process models. The exploitation of the logical structure of available event log records opens up new ways to receive purpose-oriented, less complex, and more informative process models.
Original languageEnglish
Title of host publicationProceedings of the 47th Hawaii International Conference on System Sciences
EditorsRalph H. Sprague, Jr.
Place of PublicationLos Alamitos, CA
PublisherIEEE
Publication date2014
Pages3888–3897
ISBN (Electronic)9781479925049
DOIs
Publication statusPublished - 2014
Externally publishedYes
SeriesProceedings of the Annual Hawaii International Conference on System Sciences
ISSN1060-3425

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