Enhancing diversity in Top-N recommendation

In recent years it has been argued that, besides the standard accuracy metrics, other characteristics of the recommendation algorithm ought to be taken into account when evaluating recommendation performance. One such characteristic is recommendation diversity and this topic is the focus of this research project. The overall goal of the project is to examine ways to improve the diversity of recommendations while maintaining high accuracy. During the course of my work to date I have addressed the question of how best to evaluate diversification strategies and have proposed a number of new diversity enhancement algorithms.