Topic Categorization of Tamil News Articles

This project aims to develop a model in deep learning for ‘TOPIC CATEGORIZATION OF TAMIL NEWS ARTICLES’. The process of learning for regional languages such as Tamil, Hindi differs from that of English. The task of categorising Tamil news article by topic is a text classification task. Most of the applications, such as searching in web, filtering information, recognising language, readability rating, and analysis of sentiment, already use text categorization. These tasks heavily rely on neural networks. We did multiclass text classification in this study. Different techniques, ranging from machine learning to Deep Learning, are used to handle almost all NLP difficulties. Even so, language localization remains a mystery. For languages other than English, NLP issues are uncertain. Entity Extraction, prediction, classification, and OCR in sequence modelling are examples of difficulties. Because the number of individuals utilising local languages like Tamil, Hindi, Telegu in social media network is growing, it's critical to generate automatic classification process. The goal is to categorise Tamil news stories into similar subjects (Sports, Cinema, Politics). NB, CNN, SVM algorithms are implemented to classify the content of Tamil News articles based on the category done in the previous work. The performance of these algorithms are compared with RNN using Precision, Recall, F1-score are reported in this study.