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Poster
Track: Posters
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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