Quotation Bala, Saimir, Mendling, Jan, Schimak, Martin, Queteschiner, Peter. 2018. Case and Activity Identification for Mining Process Models from Middleware. In The Practice of Enterprise Modeling, Hrsg. Robert Andrei Buchmann, Dimitris Karagiannis, Marite Kirikova, 86-102. PoEM, Vienna: Springer, Cham.




Process monitoring aims to provide transparency over operational aspects of a business process. In practice, it is a challenge that traces of business process executions span across a number of diverse systems. It is cumbersome manual engineering work to identify which attributes in unstructured event data can serve as case and activity identifiers for extracting and monitoring the business process. Approaches from literature assume that these identifiers are known a priori and data is readily available in formats like eXtensible Event Stream (XES). However, in practice this is hardly the case, specifically when event data from different sources are pooled together in event stores. In this paper, we address this research gap by inferring potential case and activity identifiers in a provenance agnostic way. More specifically, we propose a semi-automatic technique for discovering event relations that are semantically relevant for business process monitoring. The results are evaluated in an industry case study with an international telecommunication provider.


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Publication's profile

Status of publication Published
Affiliation WU
Type of publication Contribution to conference proceedings
Language English
Title Case and Activity Identification for Mining Process Models from Middleware
Title of whole publication The Practice of Enterprise Modeling
Editor Robert Andrei Buchmann, Dimitris Karagiannis, Marite Kirikova
Page from 86
Page to 102
Location PoEM, Vienna
Publisher Springer, Cham
Year 2018
ISBN 978-3-030-02302-7
Open Access N


Business Process Optimization Toolkit
Bala, Saimir (Former researcher)
Mendling, Jan (Details)
Queteschiner, Peter (Phactum Softwareentwicklung GmbH, Austria)
Schimak, Martin (plexiti GmbH, Austria)
Institute for Data, Process and Knowledge Management (AE Sabou) (Details)
Research areas (Ă–STAT Classification 'Statistik Austria')
1105 Computer software (Details)
1108 Informatics (Details)
1109 Information and data processing (Details)
1127 Information science (Details)
1138 Information systems (Details)
1140 Software engineering (Details)
5367 Management information systems (Details)
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