E-Book, Englisch, 288 Seiten
ISBN: 978-0-203-49245-1
Verlag: Taylor & Francis
Format: PDF
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)
This volume enables knowledge engineers, systems analysts, designers, developers, and researchers to understand the concept of knowledge modeling with Unified Modeling Language (UML). It offers a guide to quantifying, qualifying, understanding, and modeling knowledge by providing a reusable framework that can be adopted for KMS implementation.
Following a brief history of knowledge management, the book discusses knowledge acquisition and the types of knowledge that can be discovered within a domain. It offers an overview of types of models and the concepts behind them. It then reviews UML and how to apply UML to model knowledge. The book concludes by defining and applying the Knowledge Acquisition framework via a real-world case study.
Zielgruppe
Knowledge engineers, business systems analysts, and software engineers
Autoren/Hrsg.
Fachgebiete
Weitere Infos & Material
Introduction
Notes
Knowledge Management
Overview
Knowledge Value
Knowledge-Value Tree
Knowledge Management Systems
Knowledge Acquisition
Knowledge Acquisition Process
What is Knowledge?
Declarative Knowledge
Declarative Knowledge Learning
Declarative Knowledge Representation
Gathering Declarative Knowledge
Methods for Eliciting Declarative Knowledge
Procedural Knowledge
Process Maps
Process Defined
Capturing Procedural Knowledge
Declarative and Procedural Knowledge
Declarative Knowledge and Procedural Knowledge Difference
Tacit Knowledge
Varieties of Tacit Knowledge
Tacit Knowledge and Explicit Belief
Tacit Knowledge Capture
Tacit Knowledge as a Source of Competitive Advantage
Explicit Knowledge
Literature
Capturing Explicit Knowledge for Knowledge Management Systems
Business Value of Acquired Knowledge
Process Knowledge and Concept Knowledge
Process Knowledge
Process Knowledge Applications
Concept Knowledge
Functions of Concepts in Artificial Autonomous Agents
Representation of Concepts
The Classical View
Nonclassical Views
Discussion
The Idea of a Composite Structure
How Should the Components be Represented?
Case-Based Reasoning
Case-Based Problem Solving
Fundamentals of Case-Based Reasoning Methods
Case-Based Reasoning Problem Areas
Representation of Cases
The Dynamic Memory Model
Knowledge Modeling
Concepts
Instances
Processes (Tasks, Activities)
Attributes and Values
Rules
Relationships (Relations)
Knowledge Objects
Knowledge Base
Object Review
Common Problems
Knowledge Models
Network Diagrams
Conditions, Actions, and Events
Tables and Grids
Forms
Frames
Timeline
Matrix
Decision Trees
UML - An Introduction
A Brief History
Use Case Diagram
Actor Relationships
Activity Flow Diagram
Statechart Diagram
Collaboration Diagram
Class Diagram
Object Diagram
Knowledge Modeling with UML
UML Applied to Knowledge Models
UML to Create Knowledge Models
Concept Map
Process Map
State Transition Network
Decision Trees
Defining a Knowledge Acquisition Framework
Knowledge Acquisition Workflow
Architecture Design
Notional Output to User
Probing Questions
Knowledge Acquisition Framework
User
Decomposing the Knowledge Acquisition Task
Business Case: Department of Motor Vehicles Reporting
System
DMV Reporting System Overview
Business Scenarios
Approach
Applying Your Knowledge Framework
Determine Domain Area
Decompose the Knowledge
Determine Interdependencies
Recognize Knowledge Patterns
Determine Judgments in Knowledge
Perform Conflict Resolution
Construct the Knowledge Management System
DMV Knowledge Models
Summary
Establish Your Framework
Knowledge Modeling
Benefits
Current Environment
Knowledge Acquisition Tools
Appendices
A Probing Questions
B Glossary
C References
