An entropy-based uncertainty measure of process models

Authors:
Jae-Yoon Jung;Chang-Ho Chin;Jorge Cardoso
Affiliations:
Department of Industrial and Management Systems Engineering, Kyung Hee University, Republic of Korea;Department of Industrial and Management Systems Engineering, Kyung Hee University, Republic of Korea;CISUC/Department of Informatics Engineering, University of Coimbra, Portugal
Venue:
Information Processing Letters
Year:
2011

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Abstract

In managing business processes, the process uncertainty and variability are significant factors causing difficulties in prediction and decision making, which evokes and augments the importance and need of process measures for systematic analysis. We propose an entropy-based process measure to quantify the uncertainty of business process models. The proposed measure enables capturing the dynamic behavior of processes, in contrast to previous work which focused on providing measures for the static aspect of process models.