Computational Intelligence for Semantic Knowledge Management. New Perspectives for Designing and Organizing Information Systems.

Acampora, G. et al. (Eds.)

ISBN 10: 3030237583 / ISBN 13: 9783030237585

Editore: Cham, Springer., 2020

Riguardo questo articolo

xviii, 135 p. Hardcover. Versand aus Deutschland / We dispatch from Germany via Air Mail. Einband bestoßen, daher Mängelexemplar gestempelt, sonst sehr guter Zustand. Imperfect copy due to slightly bumped cover, apart from this in very good condition. Stamped. Sprache: Englisch.

Codice articolo 9271JB

Dati bibliografici

• Titolo: Computational Intelligence for Semantic Knowledge Management. New Perspectives for Designing and Organizing Information Systems.
• Editore: Cham, Springer.
• Data di pubblicazione: 2020
• Lingua: Inglese
• ISBN 10: 3030237583
• ISBN 13: 9783030237585
• Rilegatura: Rilegato
• Cataloghi dei venditori:
  • Informatik

Descrizione articolo

Riassunto

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.