Abstract
Process Mining uses event logs to discover and analyse business processes, typically assumed to be static. However as businesses adapt to change, processes can be expected to change. Since one application of process mining is ensuring conformance to prescribed processes or rules, timely detection of change is important. We consider process mining in such non-stationary environments and show that using a probabilistic view of processes, timely and confident detection of change is possible.
| Original language | English |
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| Title of host publication | ESANN 2012 proceedings |
| Subtitle of host publication | European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning |
| Publisher | ESANN |
| Pages | 37-42 |
| Number of pages | 6 |
| ISBN (Electronic) | 9782874190506 |
| ISBN (Print) | 978-2-87419-049-0 |
| Publication status | Published - 13 Jul 2012 |