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UML for Developing Knowledge Management Systems [Mīkstie vāki]

(Knowledge Systems Institute, Skokie, Illinois, USA)
  • Formāts: Paperback / softback, 288 pages, height x width: 234x156 mm, weight: 453 g
  • Izdošanas datums: 11-Sep-2019
  • Izdevniecība: CRC Press
  • ISBN-10: 0367391716
  • ISBN-13: 9780367391713
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UML for Developing Knowledge Management SystemsPalielināt
  • Formāts: Paperback / softback, 288 pages, height x width: 234x156 mm, weight: 453 g
  • Izdošanas datums: 11-Sep-2019
  • Izdevniecība: CRC Press
  • ISBN-10: 0367391716
  • ISBN-13: 9780367391713
Citas grāmatas par šo tēmu:
Permanent link: https://www.kriso.lv/db/9780367391713.html
Keywords:
UML for Developing Knowledge Management Systems provides knowledge engineers the framework in which to identify types of knowledge and where this knowledge exists in an organization. It also shows ways in which to use a standard recognized notation to capture, or model, knowledge to be used in a knowledge management system (KMS).

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.
Preface xiii
Acknowledgments xvii
1 Introduction
1(8)
Notes
1(8)
2 Knowledge Management
9(18)
Overview
9(2)
Knowledge Value
11(1)
Knowledge-Value Tree
12(2)
Knowledge Management Systems
14(1)
Knowledge Acquisition
14(3)
Knowledge Acquisition Process
17(8)
Subject Matter Experts
17(1)
Knowledge Acquisition Tasks
18(1)
An Iterative Approach
19(1)
Roles of Knowledge Acquisition Team Members
19(1)
Role of the Subject Matter Expert
19(1)
Role of the Knowledge Engineer
20(1)
Issues in Knowledge Acquisition
20(1)
Knowledge Acquisition Techniques
21(1)
Differential Access Hypothesis
22(1)
Comparison of Knowledge Acquisition Techniques
22(1)
Typical Use of Knowledge Acquisition Techniques
22(2)
Recent Developments
24(1)
What Is Knowledge?
25(1)
Notes
26(1)
3 Declarative Knowledge
27(16)
Declarative Knowledge Learning
28(1)
Declarative Knowledge Representation
29(1)
An Example
30(1)
Gathering Declarative Knowledge
30(2)
Methods for Eliciting Declarative Knowledge
32(9)
Note
41(2)
4 Procedural Knowledge
43(12)
Process Maps
45(1)
Process Defined
46(2)
Requirements for Representing Procedural Knowledge
46(1)
Visual Representation
46(1)
Programs
47(1)
Capturing Procedural Knowledge
48(2)
Process Definition
48(1)
Usage
49(1)
Activity
49(1)
Usage
49(1)
Transition
49(1)
Declarative and Procedural Knowledge
50(1)
Declarative Knowledge and Procedural Knowledge Difference
51(2)
Notes
53(2)
5 Tacit Knowledge
55(14)
Varieties of Tacit Knowledge
56(2)
Tacit Knowledge and Explicit Belief
58(1)
Tacit Knowledge Capture
59(5)
Pros and Cons of Using a Single Expert
61(1)
Pros and Cons of Using Multiple Experts
61(1)
Developing Relationships with Experts
62(1)
Styles of Expert Expression
62(1)
Approaching Multiple Experts
62(1)
Analogies and Uncertainties in Information
63(1)
Things to Consider during the Interview Process
63(1)
Types of Interviews
63(1)
Variations of Structured Questions
63(1)
Guidelines to Consider for Successful Interviewing
64(1)
What Things to Avoid during the Interview Session
64(1)
Tacit Knowledge as a Source of Competitive Advantage
64(3)
Innovation Process: Diversion and Conversion of Ideas
65(1)
Managing Tacit Knowledge
65(1)
Brainstorming
66(1)
Concept Extraction
66(1)
Automatic Categorization
67(1)
Notes
67(2)
6 Explicit Knowledge
69(8)
Literature
70(3)
Company Policy Manuals and Regulations
71(1)
Reports, Memos, and Guidelines
71(1)
Published Books and Journal Articles
71(1)
Existing Application Code
71(1)
Database-Stored Procedures
72(1)
Program Source Code
72(1)
Acquiring Explicit Knowledge
72(1)
Capturing Explicit Knowledge for Knowledge Management Systems
73(2)
Business Value of Acquired Knowledge
75(1)
Notes
76(1)
7 Process Knowledge and Concept Knowledge
77(12)
Process Knowledge
77(2)
Process Knowledge Applications
79(1)
Concept Knowledge
80(1)
Functions of Concepts in Artificial Autonomous Agents
81(1)
Representation of Concepts
81(1)
The Classical View
82(1)
Nonclassical Views
82(2)
Discussion
84(1)
The Idea of a Composite Structure
85(1)
How Should the Components Be Represented?
86(1)
Notes
87(2)
8 Case-Based Reasoning
89(18)
Case-Based Problem Solving
90(2)
Learning in Case-Based Reasoning
91(1)
Combining Cases with Other Knowledge
91(1)
History of the Case-Based Reasoning Field
91(1)
Fundamentals of Case-Based Reasoning Methods
92(3)
Exemplar-Based Reasoning
93(1)
Instance-Based Reasoning
93(1)
Memory-Based Reasoning
94(1)
Case-Based Reasoning
94(1)
Analogy-Based Reasoning
94(1)
Case-Based Reasoning Problem Areas
95(1)
Representation of Cases
95(1)
The Dynamic Memory Model
96(10)
Case Retrieval
97(1)
Identify Feature
98(1)
Initially Match
98(1)
Select
99(1)
Case Reuse
100(1)
Copy
100(1)
Adapt
100(1)
Case Revision
101(1)
Evaluate Solution
101(1)
Repair Fault
102(1)
Case Retainment --- Learning
102(1)
Extract
102(1)
Indexing
103(1)
Integrate
104(1)
Integrated Approaches
104(2)
Note
106(1)
9 Knowledge Modeling
107(34)
Concepts
108(1)
Instances
108(1)
Processes (Tasks, Activities)
108(1)
Attributes and Values
109(1)
Rules
109(1)
Relationships (Relations)
109(1)
Knowledge Objects
109(4)
Information Components of a Knowledge Object
110(1)
Parts Component of a Knowledge Object
111(1)
Properties Component of a Knowledge Object
111(1)
Kinds Component of a Knowledge Object
112(1)
Knowledge Base
113(1)
Creating Objects
113(1)
Object Review
114(1)
Common Problems
114(2)
Statements vs. Sentences
114(1)
Fact Statements
115(1)
Change Statements
115(1)
Goal-Fix Relationship
115(1)
Symptom-Fix Relationship
115(1)
Cause-Fix Relationship
115(1)
Knowledge Models
116(3)
Ladders
116(1)
Concept Ladder
116(1)
Composition Ladder
116(2)
Decision Ladder
118(1)
Attribute Ladder
118(1)
Process Ladder
118(1)
Network Diagrams
119(10)
Concept Map
119(2)
Epistemological Foundations
121(1)
Constructing Good Concept Maps
122(1)
Concept Maps for Evaluation
123(1)
Process Map
124(1)
Process Defined
124(1)
Process Map
124(1)
State Transition Network
125(2)
What Are States?
127(1)
Active and Passive States
128(1)
Start and End States
128(1)
Transitions
128(1)
Transitions and Active States
128(1)
Conditions, Actions, and Events
129(1)
Conditions
129(1)
Actions
130(1)
Events
130(1)
Tables and Grids
130(1)
Forms
130(1)
Frames
131(1)
Timeline
132(1)
Matrix
133(1)
Decision Trees
134(5)
Occam's Razor (Specialized to Decision Trees)
134(1)
Diagram
135(1)
Problems Suited for Decision Trees
135(1)
Understanding the Output
136(1)
When to Stop
137(1)
Pruning Trees
138(1)
Testing a Tree
138(1)
Notes
139(2)
10 UML --- An Introduction
141(24)
A Brief History
141(1)
Use Case Diagram
142(3)
Semantics
142(1)
Notation
143(1)
Mapping
144(1)
Actor Relationships
145(1)
Semantics
145(1)
Activity Flow Diagram
146(9)
Semantics
148(1)
Activity Diagram Notation
148(1)
Action States and Activity States
149(1)
Activity Diagrams with Swimlanes
150(1)
Notation
150(1)
Sequence Diagram
151(1)
Object Lifeline
152(1)
Semantics
152(1)
Notation
153(1)
Flow of Control
153(2)
Presentation Options
155(1)
Statechart Diagram
155(3)
Semantics
156(1)
Notation
156(1)
States
156(1)
Notation
157(1)
Collaboration Diagram
158(2)
Semantics
158(2)
Class Diagram
160(2)
Semantics
161(1)
Notation
161(1)
Mapping
162(1)
Object Diagram
162(3)
11 Knowledge Modeling with UML
165(18)
UML Applied to Knowledge Models
166(9)
Knowledge Use Case Model
167(1)
Knowledge Use Case Specification
168(3)
Knowledge Production Use Cases
171(1)
Information Acquisition
171(1)
Knowledge Claim Formulation
171(1)
Knowledge Claim Validation
172(1)
Knowledge Integration Use Cases
172(1)
Searching and Retrieving Stored Data, Information, or Knowledge
172(1)
Broadcasting
173(1)
Sharing
173(1)
Teaching
173(1)
Knowledge Management Use Cases
173(1)
Leadership
173(1)
Building External Relationships
174(1)
Knowledge Management Knowledge Production
174(1)
Knowledge Management Knowledge Integration
174(1)
Crisis Handling
174(1)
Changing Knowledge-Processing Rules
174(1)
Allocating Resources
175(1)
UML to Create Knowledge Models
175(2)
Concept Ladder
175(1)
Composition Ladder
176(1)
Decision Ladder
176(1)
Attribute Ladder
176(1)
Process Ladder
177(1)
Network Diagrams
177(1)
Concept Map
177(1)
Process Map
178(1)
State Transition Network
179(2)
Decision Trees
181(1)
Notes
182(1)
12 Defining a Knowledge Acquisition Framework
183(18)
Knowledge Acquisition Workflow
184(4)
Architecture Design
188(1)
Notional Output to User
189(1)
Probing Questions
189(1)
Knowledge Acquisition Framework
190(5)
Determine Domain Area
190(1)
Desirable Task
191(1)
Payoff
191(1)
Customer Management
191(2)
System Designer
193(1)
Domain (Business) Expert
194(1)
User
195(2)
Decomposing the Knowledge Acquisition Task
197(3)
Determine Interdependencies
197(1)
Focus on Pattern Recognition as the Basis of Expertise
197(1)
Qualitative Reasoning about Uncertainty and Fuzzy Logic
198(2)
Notes
200(1)
13 Business Case: Department of Motor Vehicles Reporting System
201(6)
DMV Reporting System Overview
202(1)
Business Scenarios
202(3)
Policy Level Insurance Reporting
202(1)
Insurer Level Insurance Reporting
202(1)
Vehicle Level Insurance Reporting
203(1)
Auto Fix Errors
204(1)
Approach
205(2)
14 Applying Your Knowledge Framework
207(18)
Determine Domain Area
208(1)
Decompose the Knowledge
208(1)
Determine Interdependencies
209(1)
Recognize Knowledge Patterns
209(1)
Determine Judgments in Knowledge
210(1)
Perform Conflict Resolution
210(1)
Construct the Knowledge Management System
210(1)
Results of Business Case --- DMV Reporting System
211(1)
DMV Knowledge Models
211(14)
Apply Error Determination Rules
211(5)
Determine Fines
216(1)
Apply Business Rules
217(8)
15 Summary
225(8)
Establish Your Framework
226(1)
Knowledge Modeling
227(1)
Benefits
228(1)
Current Environment
228(1)
Knowledge Acquisition Tools
229(3)
Acquire
229(1)
CommonKADS
229(1)
Epistemics
230(1)
Expect --- An Integrated Environment for Knowledge Acquisition
230(1)
Protege-2000
231(1)
Notes
232(1)
Appendices
A Probing Questions
233(16)
B Glossary
249(8)
C References
257(2)
Index 259
Rhem, Anthony J.