Survey on Recommender System Using Deep Learning Networks


  • Sushma Jaiswal Guru Ghasidas Central University, Bilaspur (C.G.), India
  • Tarun Jaiswal Department of Computer Applications, NIT Raipur, Raipur, India



deep learning, recommender system, collaborative filtering, issues, personalized recommender system, modern recommender system


In today’s times, the recommended system is a very powerful weapon of shoppers that is very helpful in advancing the Internet, personalized tendencies, and online shopping. The recommended system is used primarily for commercial benefit. The recommended system works on the strength of the user’s past shopping experience and its feedback, whether it is positive or negative. Hence the recommended system is also an innovative method. There is a deferred method of the recommended system which has its own advantages and disadvantages. In this paper, the recommender system based on deep learning is proposed, and also discussed the challenges and issues which are related to the deep learning based recommender system. i.e., Accuracy, Cold Start Problem, Scalability States etc. In this paper, we have also discussed the work done so far, which has been given by various scientists, researchers and investigators. Advancement of machine learning and deep learning is very big, in today’s era. This study will help the Researcher to move forward.




How to Cite

Sushma Jaiswal, Tarun Jaiswal. Survey on Recommender System Using Deep Learning Networks. Artificial Intelligence Evolution [Internet]. 2020 Jul. 24 [cited 2024 Jul. 13];1(2):72-89. Available from: