Title: Student profiles to improve searching in e-learning systems

Authors: Oriana Licchelli, Giovanni Semeraro

Addresses: Dipartimento di Informatica, Universita di Bari, Via E. Orabona 4, I-70126 Bari, Italy. ' Dipartimento di Informatica, Universita di Bari, Via E. Orabona 4, I-70126 Bari, Italy

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.

Keywords: information searching; information retrieval; digital libraries; web-based education; e-learning; online learning; student profiles; user preferences; customised searches; machine learning.

DOI: 10.1504/IJCEELL.2007.015050

International Journal of Continuing Engineering Education and Life-Long Learning, 2007 Vol.17 No.4/5, pp.392 - 401

Published online: 06 Sep 2007 *

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