Experimental Analyses of Temporal Activity-Sequencing Anomalies in Process Mining

In the research field of automated process discovery and analysis, purity event log datasets ought to be a matter vital importance success discovering sound exact models. Moreover, there exist various types anomalies that result in inaccurate models from enactment datasets. A peculiar one out these anomalies, which is core challenging issue this paper, temporal activity-sequencing anomaly critically affects overall quality discovery. This paper explores such event-log noises produced by special type inevitably formed preprocessing phase More precisely, it implements an algorithmic approach able detect filter those performing The author also carries series experimental analyses applying implemented five logs available 4TU Center for Research Data.