Evaluating the Diversity of Top-N Recommendations

In this paper we examine the diversity of recommendation algorithms, that is, their ability to recommend a broad range of relevant choices to the end-user. We tackle the question of how to evaluate recommendation algorithm diversity, critiquing methodologies that have been used in the state-of-the-art and proposing an alternative methodology that examines the extent to which the recommendation is concentrated in a sub-set of the catalogue.