Topic prerogative feature selection using multiple query examples for automatic video retrieval

Punitha, P., Jose, J. and Goyal, A. (2009) Topic prerogative feature selection using multiple query examples for automatic video retrieval. In: 32nd International ACM SIGIR Conference on Research and Development in Information Retrieval, Boston, MA, USA, 19-23 Jul 2009, pp. 804-805. ISBN 9781605584836 (doi: 10.1145/1571941.1572137)

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Publisher's URL: http://dx.doi.org/10.1145/1571941.1572137

Abstract

Well acceptance of relevance feedback and collaborative systems has given the users to express their preferences in terms of multiple query examples. The technology devised to utilize these user preferences, is expected to mine the semantic knowledge embedded within these query examples. In this paper, we propose a video mining framework based on dynamic learning from queries, using a statistical model for topic prerogative feature selection. The proposed method is specifically designed for multiple query example scenarios. The effectiveness of the proposed framework has been established with an extensive experimentation on TRECVid2007 data collection. The results reveal that our approach achieves a performance that is in par with the best results for this corpus without the requirement of any textual data.

Item Type:Conference Proceedings
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Jose, Professor Joemon and Goyal, Mr Anuj
Authors: Punitha, P., Jose, J., and Goyal, A.
Subjects:Z Bibliography. Library Science. Information Resources > Z665 Library Science. Information Science
Q Science > QA Mathematics > QA75 Electronic computers. Computer science
College/School:College of Science and Engineering > School of Computing Science
ISBN:9781605584836

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