Titlebook: Interacting Electrons in Nanostructures; Rolf Haug,Herbert Schoeller Conference proceedings 2001 Springer-Verlag Berlin Heidelberg 2001 He

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扫兴

FLING

science by discovering process models using event logs derived from real-world data. Besides mandatory event attributes like case identifier, activity, and timestamp, additional event attributes can be present, such as human resources, costs, and laboratory values. These event attributes can be mod

步兵

sperse

Tobias Brandesher information artefacts may exist concurrently for the same business activity. In this paper, we investigate integrating business process models and business rules. Prior literature presents three such approaches, namely text annotation, diagrammatic, and link integration. We evaluate these approa

instill

Mahn-Soo Choi,C. Bruder,Daniel Lossdizing business processes are based on manually created “de-jure” process models, which are distorted, error-prone, simplistic, and often deviating from process reality. Theoretically embedded in the organizational contingency theory as kernel theory, this paper employs a design science approach to

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微尘

Dmitri S. Golubev,Andrei D. Zaikinher information artefacts may exist concurrently for the same business activity. In this paper, we investigate integrating business process models and business rules. Prior literature presents three such approaches, namely text annotation, diagrammatic, and link integration. We evaluate these approa

bonnet

Jean-Philippe Bourgoindizing business processes are based on manually created “de-jure” process models, which are distorted, error-prone, simplistic, and often deviating from process reality. Theoretically embedded in the organizational contingency theory as kernel theory, this paper employs a design science approach to

altruism

R. Egger,A. Bachtold,M. S. Fuhrer,M. Bockrath,D. H. Cobden,P. L. McEuendepends on the prediction quality and the explainability of the prediction results. Both, prediction quality and explainability, can be influenced by unseen behavior, i.e., events that have not been observed in the training data so far. Unseen behavior can be caused by, for example, concept drift. E