Time Series Petri Net Models - Enrichment and Prediction

Rogge-Solti, Andreas and Vana, Laura and Mendling, Jan (2015) Time Series Petri Net Models - Enrichment and Prediction. In: Proceedings of the 5th International Symposium on Data-driven Process Discovery and Analysis SIMPDA 2015, December 9-11. CEUR Workshop Proceedings, Vienna. pp. 109-123.

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Abstract

Operational support as an area of process mining aims to predict the temporal performance of individual cases and the overall business process. Although seasonal effects, delays and performance trends are well-known to exist for business processes, there is up until now no prediction model available that explicitly captures this. In this paper, we introduce time series Petri net models. These models integrate the control flow perspective of Petri nets with time series prediction. Our evaluation on the basis of our prototypical implementation demonstrates the merits of this model in terms of better accuracy in the presence of time series effects.

Item Type:	Book Section
Additional Information:	Copyright © 2015 for the individual papers by the papers' authors. Copying permitted only for private and academic purposes. This volume is published and copyrighted by its editors. This work was partially supported by the European Union's Seventh Framework Programme (FP7/2007-2013) grant 612052 (SERAMIS).
Keywords:	Predictive analytics, business intelligence, time series, Petri nets
Version of the Document:	Published
Depositing User:	Gertraud Novotny
Date Deposited:	25 Jan 2017 12:45
Last Modified:	14 Sep 2018 04:55
Related URLs:	http://ceur-ws.org/Vol-1527/ http://ceur-ws.org
FIDES Link:	https://bach.wu.ac.at/d/research/results/73914/
URI:	https://epub.wu.ac.at/id/eprint/5394

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