Research on news text classification based on RCNN

Abstract

One of the popular directions of natural language processing is text processing, which is an effective method used to manage data, and it has developed rapidly after the rise of artificial intelligence. However, text classification based on traditional machine learning algorithms encountered bottlenecks in the development process, and after deep learning, a multi-level neural network, was introduced, it was soon widely used in natural language processing problems, making many branches of the field develop further, and now deep learning is the mainstream model in the field of text classification. In this paper, we first introduce the general process of text classification, point out the current problems of text classification based on traditional machine learning, and then describe the superiority of deep learning in this aspect of feature extraction. After that, three different deep learning models are experimented, and the differences between the trained models are compared and the relative optimal models are derived. Finally, the future trends and research directions of deep learning in this field are discussed.