A Novel Approach Towards News Category Prediction using NLP

The manner that people receive information has changed substantially as a result of technology’s enormous influence on society. A well-known and common service is news. The way news is created, received, and broadcast has significantly changed as a result of recent technology breakthroughs. It has made it possible for cellphones to get more frequent and real-time news information at all times. People now anticipate hearing about topics that interest them immediately. Based on content/information type, the news category predictor seeks to identify and classify various articles. Processing a large number of articles requires the automatic news categorization to be used effectively. In order to swiftly determine where they are concentrated, it can categorize and label the news pieces by evaluating the content (i.e., extracting feature values), enabling effective and rapid news delivery. Furthermore, news websites may improve their exposure by creating a recommendation system that proposes or recommends pertinent content to draw in more visitors.The main motive of the paper is to use natural language processing and find the category of the news from the data using the intrinsic NLP accuracy metrics.