Footnote:
Nach Informationen von SSRN wurde die ursprüngliche Fassung des Dokuments August 24, 2021 erstellt
Description:
With the explosive growth of Internet over last few years it is seen that there is a tremendous increase in the e-commerce business. The popularity of online shopping has increased the number of user on the web. With the increase in users over the web it becomes very critical for the e-commerce businesses to recommend products depending on the user requirements. These e-commerce companies allow user to give their opinion on the products these opinions can be viewed by other user and decide whether or not to buy it. This has given rise to the advent ofRecommender systems. A recommender system recommends the best possible product to the user depending on user interest. Deep learning on the other hand is used to continuously train and improve the accuracy of the system by using the training data so that the user always gets the best possible recommendations. In this paper a framework for creating a recommender system is proposed. This framework is based on Deep Learning Recurrent Neural Network Modelwhich reduces dimensions and thereby improves scalability and accuracy