Comparative Study on Traditional Recommender Systems and Deep Learning Based Recommender Systems

Comparative Study on Traditional Recommender Systems and Deep Learning Based Recommender Systems

N.L. AnanthaBhanu P. Bathula

Acharya Nagarjuna University, Department of IT, VFSTR University, Vadlamudi, Guntur 522213, India

Department of CSE, Thirumala Engineering College, Jonnalagadda (V), Narasaraopet-522601, Andhra Pradesh, India

Corresponding Author Email: 
anlakshmipathi@gmail.com
Page: 
64-69
|
DOI: 
https://doi.org/10.18280/ama_b.610202
Received: 
17 April 2018
|
Accepted: 
4 June 2018
|
Published: 
30 June 2018
| Citation

OPEN ACCESS

Abstract: 

Recommender systems is a big breakthrough for the field of e-commerce. Product recommendation is challenging task to e-commerce companies. Traditional Recommender Systems provided the solutions in recommending the products. This in turn help companies to generate good revenue. Now a day Deep Learning is using in every domain. Deep Learning techniques in the field of Recommender Systems can be directly applied. Deep Learning has ample number of algorithms. These algorithms can be used to give recommendations to users to purchase products. In this paper performance of Traditional Recommender Systems and Deep Learning-based Recommender Systems are compared.

Keywords: 

recommender systems, deep learning, item-based collaborative filtering, user-based collaborative filtering, matrix factorization

1. Introduction
2. Deep Learning Based Techniques
3. Deep Learning Based Recommender Systems
4. Conclusion & Future Work
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