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Springer Knowledge Representation and Relation Nets - Springer Series 506

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Description

Knowledge Representation and Relation Nets offers a systematic approach to organizing and teaching complex information through structured concept mapping. This book formalizes knowledge representation as an interconnected network of concepts and their relationships, enabling learners to model new knowledge based on existing understanding. By extending traditional concept mapping methods, the work provides a controlled framework for problem-solving that maintains consistency and logical organization throughout educational and practical applications. Ideal for students and professionals in computer science and artificial intelligence seeking to master structured knowledge systems and improve learning outcomes through formal representation techniques.

Key Features

Part of The Springer International Series in Engineering and Computer Science (volume 506), providing peer-reviewed academic rigour.

Introduces a formal knowledge representation method that extends concept mapping to create structured concept and relationship networks.

Develops a controlled approach to modelling new knowledge in relation to existing knowledge for effective teaching and learning.

Offers consistent problem-solving methodologies through well-organized knowledge structures and systematic representation techniques.

Covers foundational AI and machine learning concepts applicable to knowledge engineering and automated reasoning systems.

Product Specifications

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

Barcode

No barcode data available

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