Google’s Image Search Steps Forward
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May 07, 2008
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At the International World Wide Web Conference, held last
week in Beijing, China, Google’s researchers
presented a paper on PageRank for Google Images illustrating Google’s attempts
to improve search results for photos, art and graphics. The new Visual Rank
algorithm combines image-recognition software methods with techniques for
ranking images that look most similar.
Image search is a popular feature in many search engines but
the most of image searches use insufficient image information to rank the
images. For the most part, results are merely generated through the text clues
of the pages in which the image is embedded and often ignore the content of the
images.
Globally, computer scientists have made their best but the
problem with image analysis still persists. Google’s VisualRank
does not contribute in this direction. The desired functionality for search
engines to identify people or “read” activities in a photo is still unattainable.
Here is how Google’s researchers explained their approach: “Through
an iterative procedure based on the PageRank computation, a numerical weight is
assigned to each image; this measures its relative importance to the other
images being considered. The incorporation of visual signals in this process
differs from the majority of large- scale commercial-search engines in use
today.”
For the purposes of its paper, entitled “Page Rank for
Product Image Search”, Google conducted a series of experiments by retrieving
images for 2,000 of the most popular products queries in Google. Users in the
experiments felt more satisfied by the results and their relevancy.
The considerable benefits of Google’s new approach will
comprise the reduction of image duplicates in search results as well as the significant
decrease of the irrelevant images displaying for the particular query.
Since Google’s Universal Search is gaining popularity, the
new VisualRank will play its important role in SERPs. Definitely, a visual ranking
system will improve image search quality and bring additional utility to the
users because more relevant images will result in better search for everyone.
To get more on Google’s new algorithm by following the link: http://www.esprockets.com/papers/ www2008-jing-baluja.pdf
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