Data di Pubblicazione:
2022
Citazione:
Real-time probing of control-flow and data-flow in event logs / P. Ceravolo, E. Damiani, E.F. Schepis, G.M. Tavares. - In: PROCEDIA COMPUTER SCIENCE. - ISSN 1877-0509. - 197:(2022), pp. 751-758. ((Intervento presentato al 6. convegno ISICO Information Systems International Conference: 7 through 8 August 2021 tenutosi a Virtual Online nel 2021 [10.1016/j.procs.2021.12.197].
Abstract:
Traditional Process Mining offers batch analysis of business processes but does not transpose smoothly into online environments due to specific design constraints. Techniques adapted to support online analysis require peculiar adjustments that inherently restrict their focus to a single task. In this work, we extend the Concept Drift in Event Stream Framework (CDESF) tool to handle multiple attributes simultaneously. Our extension promotes CDESF to analyze both control-flow and data-flow characteristics in online event streams. Experiments used real and synthetic data for concept drift and anomaly detections. Results show that additional perspectives should be considered as they contain valuable information about processes.
Tipologia IRIS:
01 - Articolo su periodico
Keywords:
Anomaly detection; Clustering; Concept drift detection; Event stream; Online process mining;
Elenco autori:
P. Ceravolo, E. Damiani, E.F. Schepis, G.M. Tavares
Link alla scheda completa:
Link al Full Text: