By Topic

Ontology Extraction for Knowledge Reuse: The e-Learning Perspective

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

4 Author(s)
Matteo Gaeta ; Centro di Ricerca in Matematica Pura ed Applicata, Dipartimento di Ingegneria dell'Informazione e Matematica Applicata, University of Salerno, Fisciano, Italy ; Francesco Orciuoli ; Stefano Paolozzi ; Saverio Salerno

Ontologies have been frequently employed in order to solve problems derived from the management of shared distributed knowledge and the efficient integration of information across different applications. However, the process of ontology building is still a lengthy and error-prone task. Therefore, a number of research studies to (semi-)automatically build ontologies from existing documents have been developed. In this paper, we present our approach to extract relevant ontology concepts and their relationships from a knowledge base of heterogeneous text documents. We also show the architecture of the implemented system and discuss the experiments in a real-world context.

Published in:

IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans  (Volume:41 ,  Issue: 4 )