Abstract
Over the last fifteen years, a large amount of research in recommender systems was devoted to the development of algorithms that focus on improving the accuracy of recommendations. More recently, it has been proposed that accuracy is not the only factor that contributes to the quality of recommender systems. Among others, the diversity of recommendation lists has been considered as one of the additionally relevant factors. Therefore a number of algorithms were proposed to generate recommendations lists containing a diverse set of items. However, limited research has been done regarding how to position those diverse items in the list. In this paper we therefore investigate how to organize the diverse items to achieve a higher perceived quality. The results of an experimental study show that the perceived diversity of a recommendation list depends on the placement of the diverse items. Placing the diverse items dispersedly or together at the bottom of the list can increase the perceived diversity. In addition, we found that in the movie domain including diverse items in the recommendation list does not hurt user satisfaction, which means that recommender system providers have some flexibility to add some extra items to the lists, for example to increase the serendipity of the recommendations.