Knowledge Extraction from Events Flows

C 2012

Knowledge Extraction from Events Flows

MAHDIRAJI, Alireza Rezaei; Bruno ROSSI; Alberto SILLITTI a Giancarlo SUCCI

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

Označené pro přenos do RIV

ISBN

978-3-642-31738-5

DOI

https://doi.org/10.1007/978-3-642-31739-2_11

Příznaky

Mezinárodní význam, Recenzováno

Změněno: 20. 11. 2019 09:59, doc. Bruno Rossi, PhD

Anotace

V originále

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.

Citovat

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://doi.org/10.1007/978-3-642-31739-2_11.

@inbook{1202160,
   author = {Mahdiraji, Alireza Rezaei and Rossi, Bruno and Sillitti, Alberto and Succi, Giancarlo},
   address = {Berlin Heidelberg},
   booktitle = {Methodologies and Technologies for Networked Enterprises},
   doi = {https://doi.org/10.1007/978-3-642-31739-2_11},
   editor = {Anastasi, Giuseppe and Bellini, Emilio and Di Nitto, Elisabetta and Ghezzi, Carlo and Tanca, Letizia and Zimeo, Eugenio},
   location = {Berlin Heidelberg},
   isbn = {978-3-642-31738-5},
   pages = {221-236},
   publisher = {Springer},
   title = {Knowledge Extraction from Events Flows},
   year = {2012}
}

TY  - CHAP
ID  - 1202160
AU  - Mahdiraji, Alireza Rezaei - Rossi, Bruno - Sillitti, Alberto - Succi, Giancarlo
PY  - 2012
TI  - Knowledge Extraction from Events Flows
VL  - 7200
PB  - Springer
CY  - Berlin Heidelberg
SN  - 9783642317385
N2  - 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.
ER  -

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. \textit{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://doi.org/10.1007/978-3-642-31739-2\_{}11.

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