...Algorithms and Methods in Recommender Systems Daniar Asanov Berlin Institute of Technology Berlin, Germany Abstract—Today, there is a big veriety of different approaches and algorithms of data filtering and recommendations giving. In this paper we describe traditional approaches and explane what kind of modern approaches have been developed lately. All the paper long we will try to explane approaches and their problems based on a movies recommendations. In the end we will show the main challanges recommender systems come across. II. T RADITIONAL R ECOMMENDER A PPROACHES A. Content-based filtering Content-based recommender systems work with profiles of users that are created at the beginning. A profile has information about a user and his taste. Taste is based on how the user rated items. Generally, when creating a profile, recommender systems make a survey, to get initial information about a user in order to avoid the new-user problem. [2] In the recommendation process, the engine compares the items that were already positively rated by the user with the items he didnt rate and looks for similarities. Those items that are mostly similar to the positively rated ones, will be recommended to the user. Figure 1 shows an example of a user profile with the movies he/she has watched and the ratings the user made. Figure 2 shows the list of movies and their attribute-values. A contentbased recommender system would find out movies from the list (Figure 2) that the user has already watched and...
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