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Springer Knowledge Representation and Relation Nets 506

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Description

Knowledge Representation and Relation Nets offers a new way to organize study material into formats that are easy to teach and learn. By extending and formalizing concept mapping, this book develops knowledge representation as a structure of concepts and the specific relationships between them. This method provides a formal description of analogy, allowing for a controlled way to model new knowledge using existing knowledge. This approach is particularly useful in teaching and learning environments. By applying these methods, users gain a consistent and well-organized approach to problem solving. This text is part of the Springer International Series in Engineering and Computer Science, making it a valuable resource for those studying AI and machine learning concepts.

Key Features

Provides a fresh approach to knowledge representation for better organization of study materials.

Extends and formalizes concept mapping by building a structure of concepts and their relationships.

Uses a formal description of analogy to help model new knowledge based on existing knowledge.

Creates a controlled method for teaching and learning in various academic situations.

Delivers a consistent and well-organized approach to solving complex problems.

Product Specifications

Format
hardcover
Domain
Amazon UK
Release Date
31 May 1999
Listed Since
15 December 2006

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No barcode data available

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