Process Mining on Uncertain Event Data

arXiv (Cornell University)

Abstract

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.

Authors 1

1. Marco Pegoraro corresponding Aachen Chair of Process and Data Science (PADS) Department of Computer Science

   RWTH Aachen University

   Affiliation as printed

   Chair of Process and Data Science (PADS ) Department of Computer Science , RWTH Aachen University , Ahornstr. 55 , 52074 Aachen , Germany