Automated News Categorization using Machine Learning methods

Aegean International Textile and Advanced Engineering Conference 2018

Suleymanov, U.^1 ; Rustamov, S.^2,3

State Agy. for Pub. Service and Social Innovations under the President of the Republic of Azerbaijan, Baku, Azerbaijan^1

School of Information Technologies and Engineering, ADA University, Bakucn, Azerbaijan^2

Institute of Control Systems of ANAS, Baku, Azerbaijan^3

关键词: Chi-Squared test;    Lasso method;    Machine learning methods;    News articles;    Pre-processing;    Supervised machine learning;    Text corpora;   

Others  :  https://iopscience.iop.org/article/10.1088/1757-899X/459/1/012006/pdf
DOI  :  10.1088/1757-899X/459/1/012006

来源: IOP

【 摘 要 】

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.