<?xml version="1.0" encoding="ISO-8859-1"?><article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">
<front>
<journal-meta>
<journal-id>0187-358X</journal-id>
<journal-title><![CDATA[Investigación bibliotecológica]]></journal-title>
<abbrev-journal-title><![CDATA[Investig. bibl]]></abbrev-journal-title>
<issn>0187-358X</issn>
<publisher>
<publisher-name><![CDATA[Universidad Nacional Autónoma de México, Instituto de Investigaciones Bibliotecológicas y de la Información]]></publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id>S0187-358X2017000100103</article-id>
<article-id pub-id-type="doi">10.22201/iibi.0187358xp.2017.71.57812</article-id>
<title-group>
<article-title xml:lang="es"><![CDATA[Técnicas de aprendizaje de máquina utilizadas para la minería de texto]]></article-title>
<article-title xml:lang="en"><![CDATA[Machine Learning Techniques Used for Text Mining]]></article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Viera]]></surname>
<given-names><![CDATA[Angel Freddy Godoy]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
</contrib-group>
<aff id="Af1">
<institution><![CDATA[,Universidad Federal de Santa Catarina ¨Recuperación de la Información y Tecnología Avanzadas¨ (RITA) ]]></institution>
<addr-line><![CDATA[ ]]></addr-line>
<country>Brazil</country>
</aff>
<pub-date pub-type="pub">
<day>00</day>
<month>04</month>
<year>2017</year>
</pub-date>
<pub-date pub-type="epub">
<day>00</day>
<month>04</month>
<year>2017</year>
</pub-date>
<volume>31</volume>
<numero>71</numero>
<fpage>103</fpage>
<lpage>126</lpage>
<copyright-statement/>
<copyright-year/>
<self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_arttext&amp;pid=S0187-358X2017000100103&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_abstract&amp;pid=S0187-358X2017000100103&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_pdf&amp;pid=S0187-358X2017000100103&amp;lng=en&amp;nrm=iso"></self-uri><abstract abstract-type="short" xml:lang="es"><p><![CDATA[Resumen: Las técnicas de aprendizaje de máquina continúan siendo muy utilizadas para la minería de texto. Para este artículo se realizó una revisión de literatura en periódicos científicos publicados en los años de 2010 y 2011, con el objetivo de identificar las principales formas de aprendizaje de máquina empleadas para la minería de texto. Se utilizó estadística descriptiva para organizar, resumir y analizar los datos encontrados, y se presentó una descripción resumida de las principales encontradas. En los artículos analizados se hallaron 13 aplicadas para la minería de texto, el 83% de los artículos mencionaban de 1 a 3 técnicas de aprendizaje de máquina, las principales usadas por los autores en los artículos estudiados fueron support vector machine (SVM), k-means (K-M), k-nearest neighbors (K-NN), naive bayes (NB), self-organizing maps (SOM). Los pares que aparecen con mayor frecuencia son SVM/NB, SVM/K-NN, SVM/decission tree.]]></p></abstract>
<abstract abstract-type="short" xml:lang="en"><p><![CDATA[Abstract: The machine learning techniques are still extensively used for text mining. In this paper, there was a literature review of scientific journals published in the years 2010 and 2011, with the aim of identifying the main machine learning techniques utilized for text mining. It was possible to use descriptive and statistical techniques to organize, summarize and analyze the found data, and also, there is a shortened description of the main techniques found. Thirteen learning techniques applied to text mining appeared in the articles analyzed and 83% of the papers mentioned from 1 to 3 machine learning techniques. The main techniques used by the authors in the papers studied were support vector machine (SVM), k-means (K-M), k-nearest neighbors (K-NN), naive bayes (NB), self-organizing maps (SOM). Pairs of techniques that appear most frequently are SVM/NB, SVM/K-NN, SVM/Decision Tree and NB/K-NN.]]></p></abstract>
<kwd-group>
<kwd lng="es"><![CDATA[Aprendizaje de máquina]]></kwd>
<kwd lng="es"><![CDATA[Minería de texto]]></kwd>
<kwd lng="es"><![CDATA[Técnicas de aprendizaje de máquina]]></kwd>
<kwd lng="en"><![CDATA[Machine Learning]]></kwd>
<kwd lng="en"><![CDATA[Text Mining]]></kwd>
<kwd lng="en"><![CDATA[Machine Learning Techniques]]></kwd>
</kwd-group>
</article-meta>
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