Abstract
Traditional search engines are not efficient enough to extract useful information from scientific text databases. Therefore, it is necessary to develop advanced information retrieval software tools that allow for further classification of the scientific texts. The aim of this work is to present BioClass, a freely available graphic tool for biomedical text classification. With BioClass an user can parameterize, train and test different text classifiers to determine which technique performs better according to the document corpus. The framework includes data balancing and attribute reduction techniques to prepare the input data and improve the classification efficiency. Classification methods analyze documents by content and differentiate those that are best suited to the user requeriments. BioClass also offers graphical interfaces to get conclusions simply and easily.
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Romero, R., Vieira, A.S., Iglesias, E.L., Borrajo, L. (2014). BioClass: A Tool for Biomedical Text Classification. In: Saez-Rodriguez, J., Rocha, M., Fdez-Riverola, F., De Paz Santana, J. (eds) 8th International Conference on Practical Applications of Computational Biology & Bioinformatics (PACBB 2014). Advances in Intelligent Systems and Computing, vol 294. Springer, Cham. https://doi.org/10.1007/978-3-319-07581-5_29
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DOI: https://doi.org/10.1007/978-3-319-07581-5_29
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