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There is increasing awareness in the Recommender Systems field that diversity is a key property that enhances the usefulness of recommendations. Genre information can serve as a means to measure and enhance the diversity of recommendations and is readily available in domains such as movies, music or books. In this work we propose a new Binomial framework for defining genre diversity in recommender systems that takes into account three key properties: genre coverage, genre redundancy anddoi:10.1145/2645710.2645743 dblp:conf/recsys/VargasBKC14 fatcat:cvryyozhcngcrmpjmxqo3odgai