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Knowledge representation and relation nets 1st Edition by Aletta Geldenhuys, Hendrik van Rooyen, Franz Stetter ISBN 9781461540540 1461540542

Name: Knowledge representation and relation nets 1st Edition by Aletta Geldenhuys, Hendrik van Rooyen, Franz Stetter ISBN 9781461540540 1461540542
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SKU: EB-19522 Category: eBook PDF Tags: Aletta Geldenhuys, Franz Stetter, Hendrik van Rooyen, Knowledge representation

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Cover image: Knowledge Representation and Relation Nets
Product details:
ISBN 10: 1461540542
ISBN 13: 9781461540540
Author: Aletta Geldenhuys, Hendrik van Rooyen, Franz Stetter

Knowledge Representation and Relation Nets introduces a fresh approach to knowledge representation that can be used to organize study material in a convenient, teachable and learnable form. The method extends and formalizes concept mapping by developing knowledge representation as a structure of concepts and the relationships among them. Such a formal description of analogy results in a controlled method of modeling `new’ knowledge in terms of `existing’ knowledge in teaching and learning situations, and its applications result in a consistent and well-organized approach to problem solving. Additionally, strategies for the presentation of study material to learners arise naturally in this representation. While the theory of relation nets is dealt with in detail in part of this book, the reader need not master the formal mathematics in order to apply the theory to this method of knowledge representation. To assist the reader, each chapter starts with a brief summary, and the main ideas are illustrated by examples. The reader is also given an intuitive view of the formal notions used in the applications by means of diagrams, informal descriptions, and simple sets of construction rules. Knowledge Representation and Relation Nets is an excellent source for teachers, courseware designers and researchers in knowledge representation, cognitive science, theories of learning, the psychology of education, and structural modeling.

Knowledge representation and relation nets 1st Edition Table of contents:

Part I: Foundations of Knowledge Representation

Basic Concepts in Knowledge Representation
- What is Knowledge Representation?
- Types of Knowledge: Declarative, Procedural, and Heuristic
- Techniques and Methods in Knowledge Representation
- The Role of Logic and Semantics in Knowledge Representation
Relation Nets: An Overview
- Defining Relation Nets and Their Components
- The Structure of Relation Nets
- Relationship Between Nodes, Relations, and Attributes
- Graph Theory and Its Applications in Relation Nets
Formalizing Knowledge with Relation Nets
- Encoding Information in Relation Nets
- Types of Relations and Their Significance
- Formal Properties of Relation Nets
- Case Study: Representing Simple Systems with Relation Nets

Part II: Applications of Relation Nets

Knowledge Representation in Artificial Intelligence
- The Role of Relation Nets in AI Systems
- Case Study: Expert Systems and Knowledge Representation
- Using Relation Nets for Inference and Problem Solving
- Integration of Relation Nets with Other AI Techniques
Relation Nets in Natural Language Processing
- Representing Linguistic Knowledge with Relation Nets
- Relation Nets for Syntactic and Semantic Analysis
- Case Study: NLP Applications of Relation Nets
- Relation Nets in Machine Translation and Text Understanding
Knowledge Representation in Robotics
- Representing World Knowledge for Robots
- Relation Nets in Autonomous Navigation
- Case Study: Using Relation Nets for Robot Perception and Action
- Challenges of Knowledge Representation in Robotics

Part III: Advanced Topics in Knowledge Representation

Theoretical Foundations of Relation Nets
- Formal Semantics and Syntax of Relation Nets
- Complexity of Reasoning in Relation Nets
- Soundness, Completeness, and Efficiency in Knowledge Representation
- Relation Nets and the Logic of Information Flow
Reasoning with Relation Nets
- Inference Techniques in Relation Nets
- The Role of Deductive and Inductive Reasoning
- Problem Solving Using Relation Nets
- Case Study: Automated Theorem Proving and Relation Nets
Enhancing Relation Nets with Machine Learning
- Machine Learning Techniques for Knowledge Representation
- Using Relation Nets for Feature Extraction and Classification
- Case Study: Applying Machine Learning to Knowledge in Relation Nets
- The Future of Relation Nets and AI Integration

Part IV: Practical Implementation

Implementing Relation Nets in Software
- Tools and Frameworks for Building Relation Nets
- Developing Applications Using Relation Nets
- Case Study: Building a Knowledge Base System with Relation Nets
- Best Practices for Implementing Relation Nets in AI Projects
Case Studies and Real-World Applications
- Knowledge Representation in Healthcare Systems
- Relation Nets for Decision Support Systems
- Case Study: Smart Systems and Knowledge Representation in IoT
- Future Applications of Relation Nets in Emerging Technologies