Abstract
During the last decade a huge amount of data have been shown and introduced in the Internet. Recommender systems are thus predicting the rating that a user would give to an item. Collaborative filtering (CF) techniques are the most popular and widely used by recommender systems technique, which utilize similar neighbors to generate recommendations. This paper provides the concepts, methods, applications and evaluations of the CF based on the literature review. The paper also highlights the discussion of the types of the recommender systems as general and types of CF such as; memory based, model based and hybrid model. In addition, this paper discusses how to choose an appropriate type of CF. The evaluation methods of the CF systems are also provided throughout the paper.