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The Recommendation Problem

  • Òscar CelmaEmail author
Chapter
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Abstract

Generally speaking, the reason people could be interested in using a recommender system is that they have so many items to choose from—in a limited period of time—that they cannot evaluate all the possible options. A recommender should be able to select and filter all this information to the user. Nowadays, the most successful recommender systems have been built for entertainment content domains, such as: movies, music, or books.

Keywords

Root Mean Square Error Singular Value Decomposition Recommender System Cosine Similarity Collaborative Filter 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Berlin Heidelberg 2010

Authors and Affiliations

  1. 1.BMATBarcelonaSpain

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