A Survey on Recommendation Systems using Collaborative Filtering Techniques
R. Prabakaran, J. Pradeepkandhasamy, M. Arun
Abstract
The main objective of this paper is to deal with the view of various bigdata as well as filtering approaches involved in the review of Recommendation Systems. Recommendation System is a model which has the capacity to identify the right products based on user preferences or ratings. It has a wide area of applications ranging from ecommerce industries to OTT sites such as Hotstar, Netflix etc. There are many algorithms used in recommendation system such as Content filtering, Collaborative filtering, Hybrid Filtering and Random based popularity method. Among them, Collaborative filtering techniques are the more efficient filtering techniques because of their problem-solving approach. In the era of big data, this study provides a solution to the data sparsity problem in user recommendation systems with the help of Collaborative filtering techniques.