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An investigation into weighted data fusion for content-based multimedia information retrieval

Wilkins, Peter (2009) An investigation into weighted data fusion for content-based multimedia information retrieval. PhD thesis, Dublin City University.

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Abstract

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.

Item Type:Thesis (PhD)
Date of Award:November 2009
Refereed:No
Supervisor(s):Smeaton, Alan F.
Uncontrolled Keywords:data fusion;
Subjects:Computer Science > Information storage and retrieval systems
Computer Science > Digital video
Computer Science > Image processing
Computer Science > Information retrieval
DCU Faculties and Centres:DCU Faculties and Schools > Faculty of Engineering and Computing > School of Computing
Research Initiatives and Centres > CLARITY: The Centre for Sensor Web Technologies
Use License:This item is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 3.0 License. View License
Funders:Science Foundation Ireland, European Commission under contract FP6-027026 (K-Space), European Space Agency
ID Code:14877
Deposited On:12 Nov 2009 11:34 by Alan F. Smeaton. Last Modified 12 Nov 2009 11:34

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