A Review for Recommender System Models and Deep Learning

Abstract

In the big data and data Science age, the advancement in technology accelerated the need to make a choice from a huge amount of various alternatives and this vast amount of online data is a time consuming and very tedious task. Recommendation systems (RS) are an enormous solution to solve information overload problem. Recommendation systems have caught the attention of researchers and companies recently. It can handle data with a huge amount and help the user to make a decision. In this paper we introduce an overview for the traditional recommendation systems models, the recommendation systems advantages and shortcoming, the recommendation systems challenges, common deep learning traditional technology, how deep learning-based recommendation systems works, deep learning for recommendations and open problems and the novel research trends on this field. Key words-recommender system, challenges, deep learning, RS open issues, future research directions.