A Comprehensive study on Text Classification: Application of Convolutional Neural Networks and Deep Learning methods

Abstract

Text classification is an essential part in many applications, such as web searching, information filtering, language identification and sentiment analysis such as predicting the sentiment of tweets and movie reviews, as well as classifying email as spam or not. Classifying our content and products into categories help users to easily search and navigate within website or application, Deep learning methods are proving very good at text classification. Deep learning is a set of algorithms and techniques to imitate how the human brain works, called neural networks. Different Neural networks such as Convolutional Neural Networks (CNN when used with Deep learning algorithms, like Word2Vec or GloVe , obtain better vector representations for words and also improve the accuracy of classifiers trained with traditional machine learning algorithms.The authors have made a comprehensive study on Text Classification using convolutional neural network (CNN) .The authors will discuss different models and methods and the experimental results based on variety of datasets.