A comparative study of text mining in big data analytics using deep learning and other machine learning algorithms
by Souvik Chowdhury; Shibakali Gupta
International Journal of Hybrid Intelligence (IJHI), Vol. 1, No. 2/3, 2019

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.

Online publication date: Tue, 12-Nov-2019

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Hybrid Intelligence (IJHI):
Login with your Inderscience username and password:

Username:        Password:          Forgotten your password?

Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com