DocumentCode :
2052036
Title :
Ontology Extraction from Existing Educational Content to Improve Personalized e-Learning Experiences
Author :
Capuano, Nicola ; Dell´Angelo, Luca ; Orciuoli, Francesco ; Miranda, Sergio ; Zurolo, Francesco
Author_Institution :
Centro di Ricerca in Mat. Pura e Applicata, Fisciano, Italy
fYear :
2009
fDate :
14-16 Sept. 2009
Firstpage :
577
Lastpage :
582
Abstract :
Nowadays, the use of domain ontologies in e-learning applications is rapidly increasing due to the important role they play in knowledge representation, sharing of didactical material and content personalization. However, the ontology building processes is still extremely difficult to achieve. In this paper we present a semi-automatic process based on knowledge extraction from existing SCORM educational content aimed to speed up and facilitate the realization of domain ontologies and the breakdown of SCORM packages in fine-grained, rearrangeable learning objects appropriate for building personalized e-learning experience.
Keywords :
computer aided instruction; knowledge acquisition; ontologies (artificial intelligence); SCORM educational content; SCORM package; content personalization; didactical material; domain ontology; knowledge extraction; knowledge representation; learning object; ontology building; ontology extraction; personalized e-learning experience; semiautomatic process; Educational institutions; Electric breakdown; Electronic learning; Knowledge representation; Least squares approximation; Natural language processing; Navigation; Ontologies; Packaging; Runtime environment; Ontology extraction; Ontology modeling; Personalization; e-Learning;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Semantic Computing, 2009. ICSC '09. IEEE International Conference on
Conference_Location :
Berkeley, CA
Print_ISBN :
978-1-4244-4962-0
Electronic_ISBN :
978-0-7695-3800-6
Type :
conf
DOI :
10.1109/ICSC.2009.69
Filename :
5298528
Link To Document :
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