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2015
Springer

Avoiding Over-Fitting in ILP-Based Process Discovery

4 years 5 months ago
Avoiding Over-Fitting in ILP-Based Process Discovery
The aim of process discovery is to discover a process model based on business process execution data, recorded in an event log. One of several existing process discovery techniques is the ILP-based process discovery algorithm. The algorithm is able to unravel complex process structures and provides formal guarantees w.r.t. the model discovered, e.g., the algorithm guarantees that a discovered model describes all behavior present in the event log. Unfortunately the algorithm is unable to cope with exceptional behavior present in event logs. As a result, the application of ILP-based process discovery techniques in everyday process discovery practice is limited. This paper addresses this problem by proposing a filtering technique tailored towards ILP-based process discovery. The technique helps to produce process models that are less over-fitting w.r.t. the event log, more understandable, and more adequate in capturing the dominant behavior present in the event log. The technique is imp...
Sebastiaan J. van Zelst, Boudewijn F. van Dongen,
Added 17 Apr 2016
Updated 17 Apr 2016
Type Journal
Year 2015
Where BPM
Authors Sebastiaan J. van Zelst, Boudewijn F. van Dongen, Wil M. P. van der Aalst
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