PASCAL -

KERNEL CANONICAL CORRELATION ANALYSIS WITH APPLICATIONS
Blaz Fortuna
In: SIKDD 2004 at multiconference IS 2004, 12-15 Oct 2004, Ljubljana, Slovenia.

Abstract

This paper provides an overview of Kernel Canonical Correlation Analysis. KCCA is a technique for finding common semantic features between dierent views of data. Applications on text retrieval, categorization and image retrieval based on text queries are presented.

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EPrint Type:	Conference or Workshop Item (Paper)
Project Keyword:	Project Keyword UNSPECIFIED
Subjects:	Learning/Statistics & Optimisation Information Retrieval & Textual Information Access
ID Code:	736
Deposited By:	Blaz Fortuna
Deposited On:	30 December 2004

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