Student profiles to improve searching in e-learning systems

Author: Licchelli Oriana   Semeraro Giovanni  

Publisher: Inderscience Publishers

ISSN: 1560-4624

Source: International Journal of Continuing Engineering Education and Life-Long Learnin, Vol.17, Iss.4-5, 2007-09, pp. : 392-401

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Abstract

European countries have accumulated an enormous quantity of information in Digital Libraries (DLs). Offering seamless universal access to those collections will have a formidable impact on citizens' activities. Students could use information in DLs for improving their curricula, but it is difficult to find the exact chunk of material that solves a specific problem. A possible solution is to develop technologies that learn user preferences for customising information search. This paper focuses on a system based on Machine Learning techniques, the Profile Extractor, which automatically builds student models. An experimental session has been performed, evaluating the accuracy of the system.