Using KCCA for Japanese-English cross-language information retrieval and classification
Using KCCA for Japanese-English cross-language information retrieval and classification
Kernel Canonical Correlation Analysis (KCCA) is a method of correlating linear relationship between two multidimensional variables in feature space. We applied the KCCA to the Japanese-English cross-language information retrieval and classification. The results were encouraging.
Li, Yaoyong
073211dd-f160-4e2b-b09a-a170d865140d
Shawe-Taylor, John
b1931d97-fdd0-4bc1-89bc-ec01648e928b
2004
Li, Yaoyong
073211dd-f160-4e2b-b09a-a170d865140d
Shawe-Taylor, John
b1931d97-fdd0-4bc1-89bc-ec01648e928b
Li, Yaoyong and Shawe-Taylor, John
(2004)
Using KCCA for Japanese-English cross-language information retrieval and classification.
Learning Methods for Text Understanding and Mining Workshop, , Grenoble, France.
26 - 29 Jan 2004.
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Conference or Workshop Item
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Abstract
Kernel Canonical Correlation Analysis (KCCA) is a method of correlating linear relationship between two multidimensional variables in feature space. We applied the KCCA to the Japanese-English cross-language information retrieval and classification. The results were encouraging.
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Using KCCA.pdf
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Published date: 2004
Venue - Dates:
Learning Methods for Text Understanding and Mining Workshop, , Grenoble, France, 2004-01-26 - 2004-01-29
Organisations:
Electronics & Computer Science
Identifiers
Local EPrints ID: 259592
URI: http://eprints.soton.ac.uk/id/eprint/259592
PURE UUID: 82e44ae5-08dd-44a0-98e5-6d87e1bb0174
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Date deposited: 27 Oct 2004
Last modified: 14 Mar 2024 06:27
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Contributors
Author:
Yaoyong Li
Author:
John Shawe-Taylor
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