Using Emotion to Diversify Document Rankings

Yashar Moshfeghi, Guido Zuccon, Joemon M. Jose

Abstract: The aim of this paper is to investigate the role of emotion features in diversifying document rankings to improve the effectiveness of Information Retrieval (IR) systems. For this purpose, two approaches are proposed to consider emotion features for diversification, and they are empirically tested on the TREC 678 Interactive Track collection. The results show that emotion features are capable of enhancing retrieval effectiveness.