VisualRank
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VisualRank is a system for finding and ranking images by analysing and comparing their content, rather than searching image names, Web links or other text.
On 1 May 2008 at the International World Wide Web Conference in Beijing, Google scientists Yushi Jing and Shumeet Baluja made their VisualRank work public in a paper:[1]
In this paper, we presented a system that used visual cues, instead of solely text information, to determine the rank of images. The idea was simple: find common visual themes in a set of images, and then find a small set of images that best represented those themes. The resulting algorithm wound up being PageRank, but on an entirely inferred graph of image similarities.
