News Classification System using Machine Learning Approach

As more and more sources publish a large amount of news on the Internet every day, it is necessary to categorize news articles so that users can effectively obtain information. The amount of information from print and digital media is huge, which leads to intelligent analysis of large amounts of data, all of which are large amounts of unclassified data, stored together will not give results, so we can make some decisions, so we need categorize messages and use different algorithms to assign multiple tags based on their category. Text message classification using machine learning is the process of automatically classifying message information according to predefined tags, which are based on their content and whose accuracy comes from the training message records. The research paper analyzed many algorithms to build the system, such as Naive Bayes, SVM and neural networks for classification based on machine learning algorithms. Articles are classified according to business, entertainment, politics, sports, technology and other fields. In this way, with the help of the news classification system, users can find news articles they are interested in, which saves time and eliminates news overhead.