Recommender systems: a literature survey on Recommender System

There are number of methods to recommend different items available today. Mostly people connected with social media because of availability of internet. But nowadays shortage of timing recommender system helps to the people to choose the items easily on the behalf of ratings. We reviewed these methods and found many analyzes that contain significant shortcomings. To work with recommender system we reviewed number of research articles and research papers. We found that more than half of the recommendations were used Content-based filtering. Collaborative filtering is also used to collect the recommendations. Other complimentary concepts include stereotyping, compound-based recommendations, and mixed recommendations. Content-based filter is most widely used methods in recommendation systems.