Presentation	2003/1/14 Multimedia Search Based on Non-Negative Matrix Factorization Seiji Hotta, Kiichi Urahama,
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Abstract(in English)	A method is presented for similarity search based on dimensionality reduction by Non-negative Matrix Factorization (NMF). In similarity search based on NMF, the retrieval accuracy depends on the parameters e.g. the initial values of the factor matrices, the matrix rank and the number of iterations. In our method, we set the absolute value, of elements of the orthonormal matrices obtained by Singular Value Decomposition (SVD) to the initial values of the matrices in NMF. This initialization method helps us to determine the parameters in NMF. It is verified by experiments of image and video search that the retrieval accuracy by the proposed method is better than that by Latent Semantic Analysis (ISA).
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Paper #	IE2002-142
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Committee	IE
Conference Date	2003/1/14(1days)
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Registration To	Image Engineering (IE)
Language	ENG
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Title (in English)	Multimedia Search Based on Non-Negative Matrix Factorization
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1st Author's Name	Seiji Hotta
1st Author's Affiliation	Department of Computer and Information Sciences, Nagasaki University()
2nd Author's Name	Kiichi Urahama
2nd Author's Affiliation	Faculty of Visual Communication Design, Kyuslm Institute of Design
Date	2003/1/14
Paper #	IE2002-142
Volume (vol)	vol.102
Number (no)	570
Page	pp.pp.-
#Pages	6
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