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An investigation into weighted data fusion for content-based multimedia information retrieval
Wilkins, Peter
Content Based Multimedia Information Retrieval (CBMIR) is characterised by the combination of noisy sources of information which, in unison, are able to achieve strong performance. In this thesis we focus on the combination of ranked results from the independent retrieval experts which comprise a CBMIR system through linearly weighted data fusion. The independent retrieval experts are low-level multimedia features, each of which contains an indexing function and ranking algorithm. This thesis is comprised of two halves. In the first half, we perform a rigorous empirical investigation into the factors which impact upon performance in linearly weighted data fusion. In the second half, we leverage these finding to create a new class of weight generation algorithms for data fusion which are capable of determining weights at query-time, such that the weights are topic dependent.
Keyword(s): Information storage and retrieval systems; Digital video; Image processing; Information retrieval; data fusion
Publication Date:
Type: Other
Peer-Reviewed: Unknown
Language(s): English
Contributor(s): Smeaton, Alan F.
Institution: Dublin City University
Citation(s): Wilkins, Peter (2009) An investigation into weighted data fusion for content-based multimedia information retrieval. PhD thesis, Dublin City University.
Publisher(s): Dublin City University. School of Computing; Dublin City University. CLARITY: The Centre for Sensor Web Technologies
File Format(s): application/pdf
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First Indexed: 2009-11-17 02:04:38 Last Updated: 2019-02-09 06:57:49