Process Mining on Uncertain Event Data
This addresses the need for ad-hoc analysis techniques in process science for organizations dealing with non-standard data, but it is incremental as it sets the basis and defines a future outlook rather than presenting new methods.
The paper tackles the problem of analyzing uncertain event data in process mining, which involves events with quantified attribute imprecision, by outlining a research project to develop techniques for extracting insights from such data, but it does not report specific results or numbers.
With the widespread adoption of process mining in organizations, the field of process science is seeing an increase in the demand for ad-hoc analysis techniques of non-standard event data. An example of such data are uncertain event data: events characterized by a described and quantified attribute imprecision. This paper outlines a research project aimed at developing process mining techniques able to extract insights from uncertain data. We set the basis for this research topic, recapitulate the available literature, and define a future outlook.