2004 CanonicalCorrelationAnalysisAnO

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Subject Headings: Canonical Correlation.

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Abstract

We present a general method using kernel canonical correlation analysis to learn a semantic representation to web images and their associated text. The semantic space provides a common representation and enables a comparison between the text and images. In the experiments, we look at two approaches of retrieving images based on only their content from a text query. We compare orthogonalization approaches against a standard cross-representation retrieval technique known as the generalized vector space model.

References

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 AuthorvolumeDate ValuetitletypejournaltitleUrldoinoteyear
2004 CanonicalCorrelationAnalysisAnODavid R. Hardoon
Sandor R. Szedmak
John Shawe-Taylor
Canonical Correlation Analysis: An Overview with Application to Learning Methods10.1162/08997660423218142004
AuthorDavid R. Hardoon +, Sandor R. Szedmak + and John R. Shawe-Taylor +
doi10.1162/0899766042321814 +
titleCanonical Correlation Analysis: An Overview with Application to Learning Methods +
year2004 +