Organisations have seen a rise in the volume of data correspondingto business processes being recorded. Handling process data is ameaningful way to extract relevant information from business processes with impact on the company's values. Nonetheless, businessprocesses are subject to changes during their executions, addingcomplexity to their analysis. This paper aims at evaluating currently available Process Mining tools that handle concept drifts, i.e.changes over time of the statistical properties of the events occurring in a process. We provide an in-depth analysis of these toolsbriefly comparing their differences, advantages, and disadvantages.
Comparing concept drift detection with process mining tools / N.J. Omori, G.M. Tavares, P. Ceravolo, S. Barbon - In: SBSI'19: Proceedings[s.l] : ACM, 2019. - ISBN 9781450372374. - pp. 1-8 (( Intervento presentato al 15. convegno Brazilian Symposium on Information Systems tenutosi a Aracaju nel 2019 [10.1145/3330204.3330240].
Comparing concept drift detection with process mining tools
P. Ceravolo;
2019
Abstract
Organisations have seen a rise in the volume of data correspondingto business processes being recorded. Handling process data is ameaningful way to extract relevant information from business processes with impact on the company's values. Nonetheless, businessprocesses are subject to changes during their executions, addingcomplexity to their analysis. This paper aims at evaluating currently available Process Mining tools that handle concept drifts, i.e.changes over time of the statistical properties of the events occurring in a process. We provide an in-depth analysis of these toolsbriefly comparing their differences, advantages, and disadvantages.File | Dimensione | Formato | |
---|---|---|---|
SBSI2019_Drift_Anomaly_SWP-2.pdf
accesso riservato
Tipologia:
Pre-print (manoscritto inviato all'editore)
Dimensione
827.87 kB
Formato
Adobe PDF
|
827.87 kB | Adobe PDF | Visualizza/Apri Richiedi una copia |
3330204.3330240.pdf
accesso riservato
Tipologia:
Publisher's version/PDF
Dimensione
843.96 kB
Formato
Adobe PDF
|
843.96 kB | Adobe PDF | Visualizza/Apri Richiedi una copia |
Pubblicazioni consigliate
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.