Diversity, assortment, dissimilarity, variety:A Study of diversity measures Using low level Features for video retrieval

11Citations
Citations of this article
16Readers
Mendeley users who have this article in their library.
Get full text

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.

Cite

CITATION STYLE

APA

Halvey, M., Punitha, P., Hannah, D., Villa, R., Hopfgartner, F., Goyal, A., & Jose, J. M. (2009). Diversity, assortment, dissimilarity, variety:A Study of diversity measures Using low level Features for video retrieval. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5478 LNCS, pp. 126–137). https://doi.org/10.1007/978-3-642-00958-7_14

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free