Automated News Categorization using Machine Learning methods
Date Issued
2018
Author(s)
Suleymanov, U.
Rustamov, S.
Abstract
Being one of the most linguistically rich languages, Azerbaijani has been researched
less in the context of natural language processing area. The text corpus created from Azerbaijani
news articles is designed to apply supervised machine learning approaches for the case of
automatic news labeling. Chi-squared test and LASSO methods have been implemented for
feature selection and pre-processing. The application of supervised machine learning approaches
to the text corpus allowed us to compare the performance results of well-established supervised
machine learning approaches in the domain of Azerbaijani language.
less in the context of natural language processing area. The text corpus created from Azerbaijani
news articles is designed to apply supervised machine learning approaches for the case of
automatic news labeling. Chi-squared test and LASSO methods have been implemented for
feature selection and pre-processing. The application of supervised machine learning approaches
to the text corpus allowed us to compare the performance results of well-established supervised
machine learning approaches in the domain of Azerbaijani language.