Knowledge Extraction from Events Flows

MAHDIRAJI, Alireza Rezaei, Bruno ROSSI, Alberto SILLITTI a Giancarlo SUCCI. Knowledge Extraction from Events Flows. In Anastasi, Giuseppe and Bellini, Emilio and Di Nitto, Elisabetta and Ghezzi, Carlo and Tanca, Letizia and Zimeo, Eugenio. Methodologies and Technologies for Networked Enterprises. Berlin Heidelberg: Springer, 2012, s. 221-236, 18 s. 7200. ISBN 978-3-642-31738-5. Dostupné z: https://dx.doi.org/10.1007/978-3-642-31739-2_11.

Základní údaje

• Originální název: Knowledge Extraction from Events Flows
• Autoři: MAHDIRAJI, Alireza Rezaei, Bruno ROSSI, Alberto SILLITTI a Giancarlo SUCCI.
• Vydání: Berlin Heidelberg, Methodologies and Technologies for Networked Enterprises, od s. 221-236, 18 s. 7200, 2012.
• Nakladatel: Springer

Další údaje

• Typ výsledku: Kapitola resp. kapitoly v odborné knize
• Utajení: není předmětem státního či obchodního tajemství
• ISBN: 978-3-642-31738-5
• Doi: http://dx.doi.org/10.1007/978-3-642-31739-2_11
• Příznaky: Mezinárodní význam, Recenzováno

Anotace

In this chapter, we propose an analysis of the approaches and methods available for the automated extraction of knowledge from event flows. We specifically focus on the reconstruction of processes from automatically generated events logs. In this context, we consider that knowledge can be directly gathered by means of the reconstruction of business process models. In the ArtDECO project, we frame such approaches inside delta analysis, that is the detection of differences of the executed processes from the planned models. To this end, we provide an overview of the different techniques available for process reconstruction, and propose an approach for the detection of deviations. To show its effectiveness, we instantiate the usage to the ArtDECO case study.