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Using KCCA for Japanese-English cross-language information retrieval and classification

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
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, France. 26 - 29 Jan 2004.

Record type: Conference or Workshop Item (Paper)

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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Published date: 2004
Venue - Dates: Learning Methods for Text Understanding and Mining Workshop, France, 2004-01-26 - 2004-01-29
Organisations: Electronics & Computer Science

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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: 23 Sep 2020 16:33

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