Knowledge-based configuration : from research to business cases /

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Knowledge-based Configuration incorporates knowledge representation formalisms to capture complex product models and reasoning methods to provide intelligent interactive behavior with the user. This book represents the first time that corporate and academic worlds collaborate integrating research an...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Otros Autores: Felfernig, Alexander
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Waltham, MA : Morgan Kaufmann, ©2014.
Temas:
Expert systems (Computer science)
Systèmes experts (Informatique)
Acceso en línea:Texto completo (Requiere registro previo con correo institucional)
Tabla de Contenidos:
  • Half Title; Title Page; Copyright; Contents; Acknowledgments; About the Editors ; List of Contributors ; Foreword ; Part 1: Introduction; 1 Motivation for the Book; 1.1 What Is Configuration?; 1.2 Why Use Configuration Technologies?; 1.3 Why Read This Book?; References; 2 A Short History of Configuration Technologies; 2.1 Rule-based Configurators; 2.2 Early Model-based Configurators; 2.3 Mainstream Configuration Environments; 2.4 Mass Customization Toolkits; 2.5 Conclusion; References; 3 Configuration-Related Topics; 3.1 Design; 3.2 Planning; 3.3 Recommender Systems.
  • 3.4 Software Configuration and Version Management3.5 Product Data Management; 3.6 Conclusion; References; 4 Benefits of Configuration Systems; 4.1 Introduction; 4.2 Challenges and Benefits; 4.3 Conclusion; References; 5 Overview of the Book; Part 2: Basics; 6 Configuration Knowledge Representation and Reasoning; 6.1 Introduction; 6.2 Constraint-Based Knowledge Representation; 6.2.1 Static Constraint Satisfaction; Constraint Satisfaction Problem and Solution; Configuration Task and Solution; Example: Map Configuration (Map Coloring); Example: Mobile Phone Configuration.
  • Solution Search in Static CSPsExcursus: SAT Problems; 6.2.2 Advanced CSP Approaches; Dynamic Constraint Satisfaction; Generative Constraint Satisfaction; Solution Search in Advanced CSPs; 6.3 Graphical Knowledge Representation; 6.3.1 Feature Models; Mobile Phone Feature Model: Structure; Mobile Phone Feature Model: Constraints; Mobile Phone Configuration (Solution); Semantics of Feature Models; 6.3.2 UML Configuration Models; Computer Configuration Model in UML: Structure; Computer Configuration Model in UML: Constraints; Computer Configuration (Solution).
  • 6.4 Logic-Based Knowledge Representation6.4.1 First Order Logic (FOL); Configuration Task and Solution; Semantics of UML Configuration Models; Computer Configuration (Solution) in FOL; 6.4.2 Logic-Based Configuration; Answer Set Programming; Description Logics; Hybrid Configuration; 6.5 Comparison of Knowledge Representations; 6.5.1 Evaluation Criteria; 6.5.2 Comparison of Knowledge Representations; 6.6 Conclusion; Acknowledgments; References; 7 Conflict Detection and Diagnosis in Configuration; 7.1 Introduction; 7.2 Example; 7.3 Determining Minimal Conflict Sets.
  • 7.3.1 Simple Conflict Detection7.3.2 QuickXPlain; 7.3.3 Runtime Performance of Conflict Detection Algorithms; 7.4 Determining Minimal Diagnoses; 7.4.1 Hitting Set Directed Acyclic Graph (HSDAG); 7.4.2 FastDiag; 7.4.3 Further Approaches; 7.5 Conclusion; Acknowledgments; References; 8 User Interfaces for Configuration Environments; 8.1 Introduction; 8.2 Design Principles for Configurator User Interfaces; 8.3 Technological Issues; 8.4 Usability Issues in Configurator User Interface Development; 8.5 Conclusion; Acknowledgments; References; 9 Core Capabilities of Sustainable Mass Customization.

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