Diversity in recommender systems – A survey

Diversification has become one of the leading topics of recommender system research not only as a way to solve the over-fitting problem but also an approach to increasing the quality of the user’s experience with the recommender system. This article aims to provide an overview of research done on this topic from one of the first mentions of diversity in 2001 until now. The articles ,and research, have been divided into three sub-topics for a better overview of the work done in the field of recommendation diversification: the definition and evaluation of diversity; the impact of diversification on the quality of recommendation results and the development of diversification algorithms themselves. In this way, the article aims both to offer a good overview to a researcher looking for the state-of-the-art on this topic and to help a new developer get familiar with the topic.