A comparative study of text mining in big data analytics using deep learning and other machine learning algorithms

Abstract

Text mining has become very important in modern day and has various applications, e.g., spam email classification, similar news item clustering, etc. There have been many scenarios where regression is accompanied with text mining, e.g., for predicting sales of a product of any store the product description also plays an important role. In this paper we have tried to solve text mining problems in big data analytics using deep learning methods. Deep learning on the other hand known to be strongest supervised learning method. Here we can make use of back propagation concept to harness the power. We can also use gradient descent learning method to reduce the cost function and settle to global minima. We will also do a comparative analysis of other machine learning algorithms with deep learning methods. We will also construct an rXs contingency table popularly known as Crosstab.