Apreensibilidade e Qualidade da Informação: Bases de uma Avaliação Textual Automática na Área da Saúde

  • Asdrubal Falavigna UCS
  • Carine Webber UCS
  • Fernando Abel UCS
  • Marco Koff UCS
  • Maurício Santos UCS
  • Natália Lisboa UCS

Abstract


The internet is usually employed to research health-related information. However, available texts lack proper evaluation. In this context, a systematic review of literature on the online evaluation of texts on spinal pathologies has been performed. Selected articles evaluate the quality and the readability of the texts by means of metrics widely accepted in the scientific community, which serve as a basic source to develop a hybrid software for automatic text analysis, based on Artificial Intelligence techniques.

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Klare, G. R.: The measurement of readability. Iowa: Iowa State University Press,(1963) Luger, George.F. Artificial Intelligence. Person Education, 2009,774 p.

Weiss, Sholom M., Indurkhya, Nitin, Zhang, Tong. Fundamentals of Predictive Text Mining, Springer-Verlag London, 2010.
Published
2020-02-13
FALAVIGNA, Asdrubal; WEBBER, Carine; ABEL, Fernando; KOFF, Marco; SANTOS, Maurício; LISBOA, Natália. Apreensibilidade e Qualidade da Informação: Bases de uma Avaliação Textual Automática na Área da Saúde. In: BRAZILIAN SYMPOSIUM ON COMPUTING APPLIED TO HEALTH (SBCAS), 16. , 2016, Porto Alegre. Anais [...]. Porto Alegre: Sociedade Brasileira de Computação, 2020 . p. 2617-2620. ISSN 2763-8952. DOI: https://doi.org/10.5753/sbcas.2016.9911.