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Interpreting the semantics of an image is a hard problem. However, for storing and indexing large multimedia collections,
it is essential to build systems that can automatically extract semantics from images. In this research we show how we can fuse content and context to extract semantics from digital photographs. Our experiments show that if we can properly model context associated with media, we can interpret semantics using only a part of high dimensional content data.
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