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Paper Title:
Automatic Web Image Selection with a Probabilistic Latent Topic Model

Authors:

  • Keiji Yanai(The University of Electro-Communications)

Abstract:
We propose a new method to select relevant images to the given keywords from images gathered from theWeb based on the Probabilistic Latent Semantic Analysis (PLSA) model which is a probabilistic latent topic model originally proposed for text document analysis. The experimental results shows that the results by the proposed method is almost equivalent to or outperforms the results by existing methods. In addition, it is proved that our method can select more various images compared to the existing SVM-based methods.

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