Recommendation systems and methods are disclosed that objectively determine similarities between products and quantify diversity between products for use in generating recommendations. The product interests, such as musical interests, of a user are measured based on objective characteristics of the product. Then the interests are modeled by a distribution. The resulting distribution is then used as a measure of the diversity of the user's tastes. Based on the diversity and the characteristics of other products, recommendations are then made to the user. The systems and methods may also utilize subjective information as a secondary filter to add or remove products for which such data is known.