Machine Learning Techniques Used for Text Mining
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Keywords

Machine Learning
Text Mining
Machine Learning Techniques

How to Cite

Godoy Viera, Ángel F. (2017). Machine Learning Techniques Used for Text Mining. Investigación Bibliotecológica. Archivonomía, bibliotecología información, 31(71), 103–126. https://doi.org/10.22201/iibi.0187358xp.2017.71.57812
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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.

https://doi.org/10.22201/iibi.0187358xp.2017.71.57812
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