Recommender Systems through Collaborative Filtering

Nowadays, offer more precise and reliable information to users, according with their likes, is a topic which generate great interest not only for the research community but enterprises too. Recommender systems are based in techniques, such as collaborative filtering, to present to users those items which, according with different metrics and based in their interests and similarities with other users of a system, can be seen as the most valuables. Although, almost everybody have interacted with a recommender system (such as Amazon or eBay), the internal behaviour of this kind of systems is not clear, in this way, the purpose of this work is to make an introduction of Information Recommender Systems and based on it make a review of the Collaborative Filtering Algorithms, as the most important technique in which this kind of systems are constructed.

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