Enterprise information systems, while support daily activities, typically collect data on executed processes in event logs. These data describe the temporal sequence in which activities were carried out, hiding possible parallelism and other control flows. Representing the structure of each process execution in the form of an Instance Graph, enables managers to discover valuable knowledge on enterprise behaviors. In this work, we describe BIG4ProM, a tool which implements the Building Instance Graph (BIG) algorithm. BIG4ProM exploits filtering Process Discovery algorithms implemented in ProM in order to return the set of instance graphs related to the given event log. The plug-in is conceived to support both expert and standard users.
Understanding Knowlegde-Intensive Processes: from Traces to Instance Graphs / Diamantini, Claudia; Genga, Laura; Potena, Domenico. - STAMPA. - (2016), pp. 218-221. (Intervento presentato al convegno The 2016 International Conference on High Performance Computing & Simulation (HPCS 2016) tenutosi a Innsbruck, Austria nel July 18 – 22, 2016).
Understanding Knowlegde-Intensive Processes: from Traces to Instance Graphs
DIAMANTINI, Claudia;GENGA, LAURA;POTENA, Domenico
2016-01-01
Abstract
Enterprise information systems, while support daily activities, typically collect data on executed processes in event logs. These data describe the temporal sequence in which activities were carried out, hiding possible parallelism and other control flows. Representing the structure of each process execution in the form of an Instance Graph, enables managers to discover valuable knowledge on enterprise behaviors. In this work, we describe BIG4ProM, a tool which implements the Building Instance Graph (BIG) algorithm. BIG4ProM exploits filtering Process Discovery algorithms implemented in ProM in order to return the set of instance graphs related to the given event log. The plug-in is conceived to support both expert and standard users.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
