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Automating Business Modelling : A Guide to Using Logic to Represent Informal Methods and Support Reasoning / by Yun-Heh Chen-Burger, Dave Robertson.

Por: Colaborador(es): Tipo de material: TextoTextoSeries Advanced Information and Knowledge ProcessingEditor: London : Springer London, 2005Descripción: xvii, 322 páginas 104 ilustraciones recurso en líneaTipo de contenido:
  • texto
Tipo de medio:
  • computadora
Tipo de portador:
  • recurso en línea
ISBN:
  • 9781846281068
Formatos físicos adicionales: Edición impresa:: Sin títuloClasificación LoC:
  • QA76.9.M3
Recursos en línea:
Contenidos:
From the Contents. Introduction -- Background Knowledge -- Problems and Overviews of Approach -- Logic -- Formal Support for Data Modelling -- Formal Support for Process Modelling -- Reasoning on and Executing Processes -- Knowledge Sharing and Reuse of Models -- The Use of System: KBST-BM -- Evaluation of System -- Conclusion -- Appendices - A. Generic Models from BSDM -- B. Example Models of BSDM -- C. An Industrial Model -- D. A Model for Family Restaurants -- E. A Model for Academic Environment -- F. The Formal Operators in DefBM -- G. Entity Model Rules and Guidelines -- H. Process Model Rules and Guidelines -- I. An Interpreter for User-Defined Rules -- J. Model/Rules/Guidelines By Category -- K. Test Result of Model Rules and Guidelines -- L. An Example Use of GMA -- M. Example Use of Simulator -- References -- Index.
Resumen: Enterprise Modelling (EM) methods are frequently used by entrepreneurs as an analysis tool for describing and redesigning their businesses. The resulting product, an enterprise model, is commonly used as a blueprint for reconstructing organizations and such effort is often a part of business process re-engineering and improvement initiatives. Automating Business Modelling describes different techniques of providing automated support for enterprise modelling methods and introduces universally used approaches. A running example of a business modelling method is included; providing a framework and detailed explanation as to how to construct automated support for modelling, allowing readers to follow the method to create similar support. Suitable for senior undergraduates and postgraduates of Business Studies, Computer Science and Artificial Intelligence, practitioners in the fields of Knowledge Management, Enterprise Modelling and Software Engineering, this book offers insight and know-how to both student and professional.
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From the Contents. Introduction -- Background Knowledge -- Problems and Overviews of Approach -- Logic -- Formal Support for Data Modelling -- Formal Support for Process Modelling -- Reasoning on and Executing Processes -- Knowledge Sharing and Reuse of Models -- The Use of System: KBST-BM -- Evaluation of System -- Conclusion -- Appendices - A. Generic Models from BSDM -- B. Example Models of BSDM -- C. An Industrial Model -- D. A Model for Family Restaurants -- E. A Model for Academic Environment -- F. The Formal Operators in DefBM -- G. Entity Model Rules and Guidelines -- H. Process Model Rules and Guidelines -- I. An Interpreter for User-Defined Rules -- J. Model/Rules/Guidelines By Category -- K. Test Result of Model Rules and Guidelines -- L. An Example Use of GMA -- M. Example Use of Simulator -- References -- Index.

Enterprise Modelling (EM) methods are frequently used by entrepreneurs as an analysis tool for describing and redesigning their businesses. The resulting product, an enterprise model, is commonly used as a blueprint for reconstructing organizations and such effort is often a part of business process re-engineering and improvement initiatives. Automating Business Modelling describes different techniques of providing automated support for enterprise modelling methods and introduces universally used approaches. A running example of a business modelling method is included; providing a framework and detailed explanation as to how to construct automated support for modelling, allowing readers to follow the method to create similar support. Suitable for senior undergraduates and postgraduates of Business Studies, Computer Science and Artificial Intelligence, practitioners in the fields of Knowledge Management, Enterprise Modelling and Software Engineering, this book offers insight and know-how to both student and professional.

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