Open AccessNewspaper Article Classification using Machine Learning Techniques
Author(s) -
J. Sirisha Devi,
Dr M Rama Bai,
Chandrashekar Reddy
Publication year - 2020
Publication title -
international journal of innovative technology and exploring engineering
Language(s) - English
Resource type - Journals
ISSN - 2278-3075
DOI - 10.35940/ijitee.e2753.039520
Subject(s) - newspaper , computer science , artificial intelligence , machine learning , preprocessor , convolutional neural network , naive bayes classifier , data pre processing , deep learning , support vector machine , advertising , business
Newspaper articles offer us insights on several news. They can be one of many categories like sports, politics, Science and Technology etc. Text classification is a need of the day as large uncategorized data is the problem everywhere. Through this study, We intend to compare several algorithms along with data preprocessing approaches to classify the newspaper articles into their respective categories. Convolutional Neural Networks(CNN) is a deep learning approach which is currently a strong competitor to other classification algorithms like SVM, Naive Bayes and KNN. We hence intend to implement Convolutional Neural Networks - a deep learning approach to classify our newspaper articles, develop an understanding of all the algorithms implemented and compare their results. We also attempt to compare the training time, prediction time and accuracies of all the algorithms.