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Recommender systems by means of information retrieval
2011
Proceedings of the International Conference on Web Intelligence, Mining and Semantics - WIMS '11
In this paper we present a method for reformulating the Recommender Systems problem in an Information Retrieval one. In our tests we have a dataset of users who give ratings for some movies; we hide some values from the dataset, and we try to predict them again using its remaining portion (the so-called "leave-n-out approach"). In order to use an Information Retrieval algorithm, we reformulate this Recommender Systems problem in this way: a user corresponds to a document, a movie corresponds to
doi:10.1145/1988688.1988755
dblp:conf/wims/CostaR11
fatcat:ucag2uahpjeprnmzd2mvqgjtk4