PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Combining Clustering with Canonical Correlation Analysis for Cross-Language Patent Retrieval
Yaoyong Li and John Shawe-Taylor
In: Learning Methods for Text Understanding and Mining, 26 - 29 January 2004, Grenoble, France.


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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EPrint Type:Conference or Workshop Item (Paper)
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Natural Language Processing
Theory & Algorithms
Information Retrieval & Textual Information Access
ID Code:29
Deposited By:Steve Gunn
Deposited On:09 May 2004