USE OF CONVOLUTIONAL NEURAL NETWORKS FOR THE TASK OF CLASSIFYING TEXTS

Convolutional neural networks are a powerful tool of machine learning, which is aimed at efficient recognition and classification of images. The success of using convolutional neural networks for images has given rise to many attempts to use this tool in other problems. In this paper, we study the basic methods of using convolutional neural networks for the task of classifying texts. Experiments were performed on large-scale text data, which showed that convolutional neural networks for a word classification problem can achieve a quality similar to or better than traditional methods.