Towards an evaluation framework for process mining algorithms

A. Rozinat, A.K. Alves De Medeiros, C.W. Günther, A.J.M.M. Weijters, W.M.P. Aalst, van der

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Samenvatting

Although there has been a lot of progress in developing process mining algorithms in recent years, no effort has been put in developing a common means of assessing the quality of the models discovered by these algorithms. In this paper, we outline elements of an evaluation framework that is intended to enable (a) process mining researchers to compare the performance of their algorithms, and (b) end users to evaluate the validity of their process mining results. Furthermore, we describe two possible approaches to evaluate a discovered model (i) using existing comparison metrics that have been developed by the process mining research community, and (ii) based on the so-called k-fold-cross validation known from the machine learning community. To illustrate the application of these two approaches, we compared a set of models discovered by different algorithms based on a simple example log.
Originele taal-2Engels
Plaats van productieEindhoven
UitgeverijTechnische Universiteit Eindhoven
Aantal pagina's20
ISBN van geprinte versie978-90-386-1120-4
StatusGepubliceerd - 2007

Publicatie series

NaamBETA publicatie : working papers
Volume224
ISSN van geprinte versie1386-9213

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