DocumentCode :
2553718
Title :
Reputation Metadata for Recommending Personalized e-Learning Resources
Author :
Kerkiri, Tania ; Manitsaris, Athanassios ; Mavridou, Anastasia
Author_Institution :
Univ. of Macedonia, Thessaloniki
fYear :
2007
fDate :
17-18 Dec. 2007
Firstpage :
110
Lastpage :
115
Abstract :
Enhancing the e-Learning systems with reputation, a commonly used notion in e-Commerce systems, adds value to the resource. In this paper a RDF-based e-Learning framework that is based on reputation metadata and educational standards is proposed. Morever, the model and the retrieval algorithm of a proper recommendation system are described. This system exploits reputation and description metadata to augment personalization in e-Learning systems through recommendation methods.
Keywords :
computer aided instruction; information retrieval; meta data; RDF-based e-learning framework; educational standards; personalised e-learning resources; recommendation system; reputation metadata; retrieval algorithm; Buildings; Collaboration; Electronic learning; Feedback; Filtering algorithms; Informatics; Information filtering; Information filters; Recommender systems; Resource description framework;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Semantic Media Adaptation and Personalization, Second International Workshop on
Conference_Location :
Uxbridge
Print_ISBN :
0-7695-3040-0
Type :
conf
DOI :
10.1109/SMAP.2007.32
Filename :
4414396
Link To Document :
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