Computational Intelligence for Semantic Knowledge Management (eBook, PDF)

New Perspectives for Designing and Organizing Information Systems
Redaktion: Acampora, Giovanni; Vitiello, Autilia; Vasilakos, Athanasios V.; Pedrycz, Witold

• Format: PDF

Produktbeschreibung

This book provides a comprehensive overview of computational intelligence methods for semantic knowledge management. Contrary to popular belief, the methods for semantic management of information were created several decades ago, long before the birth of the Internet. In fact, it was back in 1945 when Vannevar Bush introduced the idea for the first protohypertext: the MEMEX (MEMory + indEX) machine. In the years that followed, Bush's idea influenced the development of early hypertext systems until, in the 1980s, Tim Berners Lee developed the idea of the World Wide Web (WWW) as it is known today. From then on, there was an exponential growth in research and industrial activities related to the semantic management of the information and its exploitation in different application domains, such as healthcare, e-learning and energy management.

However, semantics methods are not yet able to address some of the problems that naturally characterize knowledge management, such as the vagueness and uncertainty of information. This book reveals how computational intelligence methodologies, due to their natural inclination to deal with imprecision and partial truth, are opening new positive scenarios for designing innovative semantic knowledge management architectures.

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Produktdetails

• Verlag: Springer-Verlag GmbH
• Seitenzahl: 135
• Erscheinungstermin: 11. Juli 2019
• Englisch
• ISBN-13: 9783030237608
• Artikelnr.: 57114465

Inhaltsangabe

Natural Noise Management in Recommender Systems using Fuzzy Tools.- Combining Collaborative Filtering and Semantic-based Techniques to Recommend Components for Mashup Design.- Semantic Maps for Knowledge Management of Web and Social Information.- A Study on Local Search Meta-heuristics for Ontology Alignment.- Decision Tree Based Single Person Gesture Recognition.- Modified Type-2 Fuzzy Gesture Space Induced Physical Disorder Recognition.- Performance Analysis.

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