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In this paper, we consider the problem of calculating fast and accurate approximations to the personalized PageRank score ([8, 16]) of a webpage. We focus on techniques to improve speed by limiting the amount of webgraph data we need to access. PageRank scores are mainly used for ranking purposes, and generally only the scores exceeding a given threshold are relevant. In practice, and relative to the size of the web, only a small number of pages have a non-negligible personalized PageRankdoi:10.1080/15427951.2006.10129128 fatcat:upj2qb3z35cp7gqgw74ndjyxny