Quotation Rogge-Solti, Andreas, Kasneci, Gjergji. 2014. Temporal Anomaly Detection in Business Processes. In Business Process Management, Hrsg. Shazia Sadiq, Pnina Soffer, Hagen Völzer, 234-249. Haifa, Israel: Springer Lecture Notes in Computer Science (LNCS).




The analysis of business processes is often challenging not only because of intricate dependencies between process activities but also because of various sources of faults within the activities. The automated detection of potential business process anomalies could immensely help business analysts and other process participants detect and understand the causes of process errors. This work focuses on temporal anomalies, i.e., anomalies concerning the runtime of activities within a process. To detect such anomalies, we propose a Bayesian model that can be automatically inferred form the Petri net representation of a business process. Probabilistic inference on the above model allows the detection of non-obvious and interdependent temporal anomalies.


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Publication's profile

Status of publication Published
Affiliation WU
Type of publication Contribution to conference proceedings
Language English
Title Temporal Anomaly Detection in Business Processes
Title of whole publication Business Process Management
Editor Shazia Sadiq, Pnina Soffer, Hagen Völzer
Page from 234
Page to 249
Location Haifa, Israel
Publisher Springer Lecture Notes in Computer Science (LNCS)
Year 2014
ISBN 978-3-319-10171-2
URL http://link.springer.com/chapter/10.1007/978-3-319-10172-9_15


Solti, Andreas (Former researcher)
Kasneci, Gjergji (Hasso-Plattner-Institut der Universität Potsdam, Germany)
Institute for Data, Process and Knowledge Management (AE Sabou) (Details)
Research areas (ÖSTAT Classification 'Statistik Austria')
5367 Management information systems (Details)
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