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).
BibTeX
Abstract
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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Status of publication | Published |
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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 |
Associations
- People
- Solti, Andreas (Former researcher)
- External
- Kasneci, Gjergji (Hasso-Plattner-Institut der Universität Potsdam, Germany)
- Organization
- Institute for Data, Process and Knowledge Management (AE Sabou) (Details)
- Research areas (ÖSTAT Classification 'Statistik Austria')
- 5367 Management information systems (Details)