Merging event logs with many to many relationships

Lihi Raichelson; Pnina Soffer

doi:10.1007/978-3-319-15895-2_28

Merging event logs with many to many relationships

Lihi Raichelson, Pnina Soffer

Department of Information Systems

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

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 language	English
Title of host publication	Business Process Management Workshops BPM 2014 International Workshops, Revised Papers
Editors	Fabiana Fournier, Jan Mendling
Publisher	Springer Verlag
Pages	330-341
Number of pages	12
ISBN (Electronic)	9783319158945
DOIs	https://doi.org/10.1007/978-3-319-15895-2_28
State	Published - 2015
Event	International Workshops on Business Process Management Workshops, BPM 2014 - Eindhoven, Netherlands Duration: 7 Sep 2014 → 8 Sep 2014

Publication series

Name	Lecture Notes in Business Information Processing
Volume	202
ISSN (Print)	1865-1348

Conference

Conference	International Workshops on Business Process Management Workshops, BPM 2014
Country/Territory	Netherlands
City	Eindhoven
Period	7/09/14 → 8/09/14

Bibliographical note

Publisher Copyright:
© Springer International Publishing Switzerland 2015.

Keywords

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

Access to Document

10.1007/978-3-319-15895-2_28

Cite this

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title = "Merging event logs with many to many relationships",

abstract = "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.",

keywords = "End-to-end process, Merging logfiles, Multiple instances, Process mining",

author = "Lihi Raichelson and Pnina Soffer",

note = "Publisher Copyright: {\textcopyright} Springer International Publishing Switzerland 2015.; International Workshops on Business Process Management Workshops, BPM 2014 ; Conference date: 07-09-2014 Through 08-09-2014",

year = "2015",

doi = "10.1007/978-3-319-15895-2_28",

language = "English",

series = "Lecture Notes in Business Information Processing",

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editor = "Fabiana Fournier and Jan Mendling",

booktitle = "Business Process Management Workshops BPM 2014 International Workshops, Revised Papers",

address = "Germany",

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Raichelson, L & Soffer, P 2015, Merging event logs with many to many relationships. in F Fournier & J Mendling (eds), Business Process Management Workshops BPM 2014 International Workshops, Revised Papers. Lecture Notes in Business Information Processing, vol. 202, Springer Verlag, pp. 330-341, International Workshops on Business Process Management Workshops, BPM 2014, Eindhoven, Netherlands, 7/09/14. https://doi.org/10.1007/978-3-319-15895-2_28

Merging event logs with many to many relationships. / Raichelson, Lihi; Soffer, Pnina.
Business Process Management Workshops BPM 2014 International Workshops, Revised Papers. ed. / Fabiana Fournier; Jan Mendling. Springer Verlag, 2015. p. 330-341 (Lecture Notes in Business Information Processing; Vol. 202).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Raichelson, Lihi

AU - Soffer, Pnina

N1 - Publisher Copyright: © Springer International Publishing Switzerland 2015.

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N2 - 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.

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ER -

Merging event logs with many to many relationships

Abstract

Publication series

Conference

Bibliographical note

Keywords

ASJC Scopus subject areas

Access to Document

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Cite this