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29 Apr 08

PageRank for Product Image Search - By Nitro PDF Software

In this paper, we cast the image-ranking problem into the
task of identifying "authority" nodes on an inferred visual
similarity graph and propose an algorithm to analyze the
visual link structure that can be created among a group
of images. 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. Commercial
search-engines often solely rely on the text clues of the pages
in which images are embedded to rank images, and often en-
tirely ignore the content of the images themselves as a rank-
ing signal. To quantify the performance of our approach in
a real-world system, we conducted a series of experiments
based on the task of retrieving images for 2000 of the most
popular products queries. Our experimental results show
significant improvement, in terms of user satisfaction and
relevancy, in comparison to the most recent Google Image
Search results.

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