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Title: Latent semantic fusion model for image retrieval and annotation
Authors: Priam, T.-T.
Maillot, N.E.
Lim, J.-H. 
Chevallet, J.-P.
Keywords: Automatic annotation
Image indexing and retrieval
Latent semantic indexing
Multimedia fusion
Issue Date: 2007
Citation: Priam, T.-T.,Maillot, N.E.,Lim, J.-H.,Chevallet, J.-P. (2007). Latent semantic fusion model for image retrieval and annotation. International Conference on Information and Knowledge Management, Proceedings : 439-444. ScholarBank@NUS Repository.
Abstract: This paper studies the effect of Latent Semantic Analysis (LSA) on two different tasks: multimedia document retrieval (MDR) and automatic image annotation (AIA). The contributions of this paper are twofold. First, to the best of our knowledge, this work is the first study of the influence of LSA on the retrieval of a significant number of multimedia documents (i.e. collection of 20000 tourist images). Second, it shows how different image representations (region-based and keypoint-based) can be combined by LSA to improve automatic image annotation. The document collections used for these experiments are the Corel photo collection and ImageCLEF 2006 collection. Copyright 2007 ACM.
Source Title: International Conference on Information and Knowledge Management, Proceedings
ISBN: 9781595938039
DOI: 10.1145/1321440.1321503
Appears in Collections:Staff Publications

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