An Automated News Text Classification Information System

Abstract

An information system for the categorization of news texts using machine learning algorithms is being planned and developed in this project. An online platform and an automated categorization system make up the data system in question. We have preprocessed the text data. In order to train classifiers using the grid search method, many experiments were carried out. We have tested four different categorization algorithms: naïve Bayesian, logistic regression, random forest, and artificial neural network. Several measures, including F-score, recall, and precision, have been used to assess the trained classifiers' classification quality. An additional goal in developing the website was to provide easy access to the information system.