News article classification of Mexican newspapers

Producción científica: Capítulo del libro/informe/acta de congresoContribución a la conferenciarevisión exhaustiva

5 Citas (Scopus)

Resumen

Articles in newspapers are divided in sections like culture, politics and sports to help readers to find information easily. Newspapers editors read the articles and decide the ones to be published and the sections they belong to. This paper presents supervised machine learning methods to automatically classify news articles in newspaper sections. To perform this task 4,027 news articles were collected along with its corresponding sections from three Mexican newspapers during a six month period. Different features were extracted and several machine learning methods were tested. Obtained results show an accuracy over 80% classifying articles in the particular sections of the three selected newspapers.

Idioma originalInglés
Título de la publicación alojadaTelematics and Computing - 7th International Congress, WITCOM 2018, Proceedings
EditoresMiguel Felix Mata-Rivera, Roberto Zagal-Flores
EditorialSpringer Verlag
Páginas101-109
Número de páginas9
ISBN (versión impresa)9783030037628
DOI
EstadoPublicada - 2018
Evento7th International Congress of Telematics and Computing, WITCOM 2018 - Mazatlán, México
Duración: 5 nov. 20189 nov. 2018

Serie de la publicación

NombreCommunications in Computer and Information Science
Volumen944
ISSN (versión impresa)1865-0929

Conferencia

Conferencia7th International Congress of Telematics and Computing, WITCOM 2018
País/TerritorioMéxico
CiudadMazatlán
Período5/11/189/11/18

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