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, 16 (12), 2639-64

Canonical Correlation Analysis: An Overview With Application to Learning Methods

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Canonical Correlation Analysis: An Overview With Application to Learning Methods

David R Hardoon et al. Neural Comput.

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.

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