Abstract
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.
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