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Titolo
A System for Multi-label Classification of Learning Objects
Autor(es)
Soggetto
Computer Science
Fecha de publicación
2011
Editore
Springer Science + Business Media
Citación
Soft Computing Models in Industrial and Environmental Applications, 6th International Conference SOCO 2011 Advances in Intelligent and Soft Computing. Advances in Intelligent and Soft Computing. Volumen 87, pp. 523-531.
Resumen
The rapid evolution within the context of e-learning is closely linked to international efforts on the standardization of Learning Object (LO), which provides ubiquitous access to multiple and distributed educational resources in many repositories. This article presents a system that enables the recovery and classification of LO and provides individualized help with selecting learning materials to make the most suitable choice among many alternatives. For this classification, it is used a special multi-label data mining designed for the LO ranking tasks. According to each position, the system is responsible for presenting the results to the end user. The learning process is supervised, using two major tasks in supervised learning from multi-label data: multi-label classification and label ranking.
URI
ISBN
978-3-642-19643-0 (Print) / 978-3-642-19644-7 (Online)
ISSN
1867-5662 (Print) / 1867-5670 (Online)
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