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At Google, the PageRank algorithm helps rankings in search results by providing measures of web page importance. This paper builds upon the distributed randomized approach for this algorithm proposed in our recent works. To reduce computation and communication, we develop a method to systematically aggregate web pages into groups by exploiting the sparsity inherent in the web. Each group computes...
The so-called PageRank algorithm has been used at Google for properly ranking search results. It quantifies the importance of each page by the structure of links in the web. In our recent work, we have proposed a distributed randomized approach for the PageRank computation, where the pages find their own values by communicating with linked pages. This paper builds upon this approach to improve the...
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