Diversity, Assortment, Dissimilarity, Variety: A Study of Diversity Measures Using Low Level Features for Video Retrieval

Authors:
Martin Halvey;P. Punitha;David Hannah;Robert Villa;Frank Hopfgartner;Anuj Goyal;Joemon M. Jose
Affiliations:
Department of Computing Science, University of Glasgow, Glasgow, Scotland G12 8QQ;Department of Computing Science, University of Glasgow, Glasgow, Scotland G12 8QQ;Department of Computing Science, University of Glasgow, Glasgow, Scotland G12 8QQ;Department of Computing Science, University of Glasgow, Glasgow, Scotland G12 8QQ;Department of Computing Science, University of Glasgow, Glasgow, Scotland G12 8QQ;Department of Computing Science, University of Glasgow, Glasgow, Scotland G12 8QQ;Department of Computing Science, University of Glasgow, Glasgow, Scotland G12 8QQ
Venue:
ECIR '09 Proceedings of the 31th European Conference on IR Research on Advances in Information Retrieval
Year:
2009

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Abstract

In this paper we present a number of methods for re-ranking video search results in order to introduce diversity into the set of search results. The usefulness of these approaches is evaluated in comparison with similarity based measures, for the TRECVID 2007 collection and tasks [11]. For the MAP of the search results we find that some of our approaches perform as well as similarity based methods. We also find that some of these results can improve the P@N values for some of the lower N values. The most successful of these approaches was then implemented in an interactive search system for the TRECVID 2008 interactive search tasks. The responses from the users indicate that they find the more diverse search results extremely useful.