DICA : Recommendation System Based on Learning Object Content

Authors

  • Felipe José Rocha Vieira Universidade Federal de Sergipe
  • Maria Augusta Silveira Netto Nunes Universidade Federal de Sergipe

Keywords:

Recommender Systems, Learning Objects, Data Mining

Abstract

There are much educational stuff on the Internet, no to mention the websites which have the sole purpose of being a repository for such resources, but still, finding stuff that help learning is a laborious, often exhausting process. This paper presents DICA - learning object recommender system - which uses information from Banco Internacional de Objetos Educacionais (BIOE) to recommend learning objects according to the similarities between them by using artificial intelligence techniques

Author Biographies

Felipe José Rocha Vieira, Universidade Federal de Sergipe

Técnico em desenvolvimento de sistemas formado pelo IFS (Instituto Federal de Educação, Ciência e Tecnologia de Sergipe) e graduando em sistemas de informação pela UFS (Universidade Federal de Sergipe). Já trabalhou no IFS, realizando atividades de suporte e desenvolvimento de software, exerceu também atividade de programador na UFS e atualmente se encontra no TJSE como programador de sistemas. Possui interesse nas áreas de Engenharia de Software, Inteligência Artificial e Sistemas de Informação, mas sempre que possível adentra em outras áreas.

Maria Augusta Silveira Netto Nunes, Universidade Federal de Sergipe

Professora Adjunta na DCOMP - Universidade Federal de Sergipe em Aracaju-Sergipe-Brasil. Membro do EDAPECI research group, GEPIED research group e Pii research group. Doutorado em Laboratoire d'Informatique, de Robotique et de Microélectronique de Montpellier na Université Montpellier II e Stefano A. Cerri foi o orientador na tese.

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Published

2012-08-06

How to Cite

Vieira, F. J. R., & Nunes, M. A. S. N. (2012). DICA : Recommendation System Based on Learning Object Content. Scientia Plena, 8(5). Retrieved from https://www.scientiaplena.org.br/sp/article/view/464

Issue

Vol. 8 No. 5 (2012): May/Maio 2012

Section

Articles

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