Diversity, assortment, dissimilarity, variety: a study of diversity measures using low level features for video retrieval

Halvey, M., Punitha, P., Hannah, D., Villa, R., Hopfgartner, F. and Jose, J.M. (2009) Diversity, assortment, dissimilarity, variety: a study of diversity measures using low level features for video retrieval. Lecture Notes in Computer Science, pp. 126-137. (doi: 10.1007/978-3-642-00958-7_14)

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.

• Item Type: Articles
• Additional Information: The original publication is available at www.springerlink.com
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Jose, Professor Joemon and Halvey, Dr Martin and Villa, Dr Robert and Hannah, Mr David
• Authors: Halvey, M., Punitha, P., Hannah, D., Villa, R., Hopfgartner, F., and Jose, J.M.
• Subjects: Q Science > QA Mathematics > QA76 Computer software
• College/School: College of Arts & Humanities > School of Humanities > Information Studies; College of Science and Engineering > School of Computing Science
• Research Group: Information Retrieval
• Journal Name: Lecture Notes in Computer Science
• ISSN: 0302-9743