Performing Text Classification and Categorization through Deep Learning and Semi-Supervised Learning

Text classification is a truly mandatory field in the world of Natural Language Processing (NLP). It involves real-life applications in domains such as engineering and computer science. It is also successful in addressing complications with labeled data. There are two particular Deep Learning (DL) algorithms that are effectively productive in text classification: Recurrent Neural Network (RNN) and Convolutional Neural Network (CNN) as well as the semi-supervised learning algorithm. This research provides a much better overview of the text in each online document being classified and categorized into an almost infinite number of different sets by the RNN, CNN, and semi-supervised learning techniques. Furthermore, it determines which method has the best and the highest accuracy. It can also identify and resolve any problems the DL and semi-supervised learning methods face using text classification/categorization.