An Application-oriented Review of Deep Learning in Recommender Systems

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Author(s)

Jyoti Shokeen 1,* Chhavi Rana 1

1. Department of CSE, UIET, M.D. University, Rohtak, 124001, India

* Corresponding author.

DOI: https://doi.org/10.5815/ijisa.2019.05.06

Received: 2 May 2018 / Revised: 10 Jun. 2018 / Accepted: 21 Jun. 2018 / Published: 8 May 2019

Index Terms

Recommender system, Deep learning, Collaborative filtering, Deep neural network, Social recommender system

Abstract

The development in technology has gifted huge set of alternatives. In the modern era, it is difficult to select relevant items and information from the large amount of available data. Recommender systems have been proved helpful in choosing relevant items. Several algorithms for recommender systems have been proposed in previous years. But recommender systems implementing these algorithms suffer from various challenges. Deep learning is proved successful in speech recognition, image processing and object detection. In recent years, deep learning has been also proved effective in handling information overload and recommending items. This paper gives a brief overview of various deep learning techniques and their implementation in recommender systems for various applications. The increasing research in recommender systems using deep learning proves the success of deep learning techniques over traditional methods of recommender systems.

Cite This Paper

Jyoti Shokeen, Chhavi Rana, "An Application-oriented Review of Deep Learning in Recommender Systems", International Journal of Intelligent Systems and Applications(IJISA), Vol.11, No.5, pp.46-54, 2019. DOI:10.5815/ijisa.2019.05.06

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