Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Computational Intelligence for Semantic Knowledge Management: New Perspectives for Designing and Organizing Information Systems
Department of Physics “Ettore Pancini”, University of Naples Federico II, Naples, Italy.
Department of Electrical and Computer Engineering, University of Alberta, Edmonton, AB, Canada.
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.ORCID iD: 0000-0003-1902-9877
Department of Physics “Ettore Pancini”, University of Naples Federico II, Naples, Italy.
2020 (English)Collection (editor) (Other academic)
Abstract [en]

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.

Place, publisher, year, edition, pages
Springer Nature, 2020. Vol. 837, p. 135p. vii-x
Series
Studies in Computational Intelligence (SCI), ISSN 1860-949X, E-ISSN 1860-9503 ; 837
National Category
Computer Sciences
Research subject
Pervasive Mobile Computing
Identifiers
URN: urn:nbn:se:ltu:diva-95333DOI: 10.1007/978-3-030-23760-8ISBN: 978-3-030-23758-5 (print)ISBN: 978-3-030-23760-8 (electronic)OAI: oai:DiVA.org:ltu-95333DiVA, id: diva2:1728853
Available from: 2023-01-19 Created: 2023-01-19 Last updated: 2023-01-19Bibliographically approved

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full text

Authority records

Vasilakos, Athanasios

Search in DiVA

By author/editor
Vasilakos, Athanasios
By organisation
Computer Science
Computer Sciences

Search outside of DiVA

GoogleGoogle Scholar

doi
isbn
urn-nbn

Altmetric score

doi
isbn
urn-nbn
Total: 92 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf