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Data-driven Process Discovery - Artificial Event Log

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posted on 2016-12-08, 00:00 authored by Felix MannhardtFelix Mannhardt
A synthetic event log with 100,000 traces and 900,000 events that was generated by simulating a simple artificial process model. There are three data attributes in the event log: Priority, Nurse, and Type. Some paths in the model are recorded infrequently based on the value of these attributes. Noise is added by randomly adding one additional event to an increasing number of traces. CPN Tools (http://cpntools.org) was used to generate the event log and inject the noise.

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Eindhoven University of Technology, Department of Mathematics and Computer Science

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Eindhoven University of Technology

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media types: application/x-gzip, application/zip, text/plain, text/xml

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    Eindhoven University of Technology

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    Keywords

    Data miningIEEE Task Force on Process MiningProcess miningSystematic data processingsynthetic event logsManagement and ProductivityBusiness and Management

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    4TU General Terms of Use

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