Alleviating the Issues of Recommendation System Through Deep Learning Techniques

Social media and other online sources generate abundance of data which leads to the problem of information overload. Recommender systems have emerged as a solution to deal with this problem which suggest items to users based on their information need. Despite the success of these systems, they also suffer from few issues such as cold start problem, sparsity, scalability, and overspecialization, among others. Although several attempts were made in the past to deal with these issues, several current recommender systems continue to face these issues. Deep learning algorithms can also be used to deal with recommendation system issues. In this paper, we discuss the issues of recommendation systems and how their impact can be alleviated through deep learning algorithms.