Integrating Business Process Models and Rules

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Empirical Evidence and Decision Framework, Lecture Notes in Business Information Processing 343

ISBN: 3030118088
ISBN 13: 9783030118082
Autor: Wang, Wei
Verlag: Springer Verlag GmbH
Umfang: xii, 127 S., 55 s/w Illustr., 8 farbige Illustr., 127 p. 63 illus., 8 illus. in color.
Erscheinungsdatum: 29.01.2019
Auflage: 1/2019
Produktform: Kartoniert
Einband: Kartoniert

This book combines multiple research methods, experiment, survey, and design science, as well as traditional measurements and neurophysiological techniques that can capture a variety of cognitive behaviors in human information processing, providing more solid and comprehended research findings. While the focus of the book is the modelling of process models and rules, the methods and techniques used in this book can also be adopted and applied to broader conceptual modelling research incorporating a variety of notations (e.g. UML, ER diagrams) or ontologies.It is a revised version of the PhD dissertation written by the author at the School of Information Technology and Electrical Engineering of the University of Queensland, Australia. In 2018, the PhD dissertation won the „CAiSE PhD Award,“ granted to outstanding PhD theses in the field of information systems engineering.

Artikelnummer: 6120602 Kategorie:

Beschreibung

This book combines multiple research methods, experiment, survey, and design science, as well as traditional measurements and neurophysiological techniques that can capture a variety of cognitive behaviors in human information processing, providing more solid and comprehended research findings. While the focus of the book is the modelling of process models and rules, the methods and techniques used in this book can also be adopted and applied to broader conceptual modelling research incorporating a variety of notations (e.g. UML, ER diagrams) or ontologies.It is a revised version of the PhD dissertation written by the author at the School of Information Technology and Electrical Engineering of the University of Queensland, Australia. In 2018, the PhD dissertation won the CAiSE PhD Award, granted to outstanding PhD theses in the field of information systems engineering.

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