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Naman Jogani10/22/2019David BellangerA Survey of Collaborative Filtering TechniquesArticle addresses the approach of collaborative filtering. This is one of the most successful approaches to building recommender systems. Collaborative filtering uses a database of preferences for items by users to predict additional topics or products a new user might like.The example of amazon and Barnes and Nobles website illuminates the memory based CF methods that are deployed into commercial systems. The reason being that they are easy to implement and customization of CF systems for each user decreases the search effort for users. However, there are certain limitations to this approach aswell. The similarity values are based on common items and therefor are unreliable when data are sparse, and the common items are therefore few. Along with that they are dependent on human ratings, and cannot recommend for new users and items.