Title: News classification using text data generators and convolutional neural network (CNN)

Authors: R. Radha; Pranav Gautam; A. Bhijit Sunil

Addresses: CSE, SRMIST, 603203, India ' CSE, SRMIST, 603203, India ' CSE, SRMIST, 603203, India

Abstract: Everyday news channels and newspaper publications receive a huge number of news updates. It is nearly impossible to read all this enormous amount of data and categorise the news accordingly. Automated News classification is a growing interest in the research of text mining and machine learning. Correctly identifying the news into particular category is still presenting challenge because of large and vast number of features in the dataset. In addition to that news updates sometimes don't have a clear distinction about their categories. Also, almost all the news updates consist of date, time and place and numbers like information about the happening which may seem important to the viewer but completely useless and instead a trouble to the classifier. In our project, we aim to overcome all these challenges to build a better classification system for the news. There are many classification algorithms that can be used to classify text.

Keywords: machine learning; SVM; support vector machine; Naïve Bayes; random forest; classification; text data generator.

DOI: 10.1504/IJSOI.2023.132369

International Journal of Services Operations and Informatics, 2023 Vol.12 No.3, pp.244 - 252

Received: 06 Aug 2022
Accepted: 13 Feb 2023
Published online: 18 Jul 2023 *

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