Correlating educational documents from different sources through graphs and taxonomies

Resumo


Digital educational documents are growing in size and variety, and scientists are facing difficulties to find their way through them. One of the initiatives that have emerged to solve this problem involves the use of automatic classification algorithms. However, it is difficult to analyze implicit relationships among topics of materials. This paper presents CIMAL, a framework for enabling flexible access to material stored in arbitrary repositories. CIMAL combines semantic classification, taxonomies and graphs to elicit relationships among topics of educational documents. We validated our work using materials from Coursera (courses offered by Johns Hopkins University and University of Michigan) and a Higher Education Institute, from Brazil.

Palavras-chave: Educational Documents, graphs, taxonomies, semantic classification

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25/08/2018
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SARAIVA, Márcio de Carvalho; MEDEIROS, Claudia Bauzer. Correlating educational documents from different sources through graphs and taxonomies. In: SIMPÓSIO BRASILEIRO DE BANCO DE DADOS (SBBD), 33. , 2018, Rio de Janeiro. Anais [...]. Porto Alegre: Sociedade Brasileira de Computação, 2018 . p. 121-132. ISSN 2763-8979. DOI: https://doi.org/10.5753/sbbd.2018.22224.