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arXiv:1002.2858cs.IR

PageRank: Standing on the shoulders of giants

Massimo Franceschet

Abstract

PageRank is a Web page ranking technique that has been a fundamental ingredient in the development and success of the Google search engine. The method is still one of the many signals that Google uses to determine which pages are most important. The main idea behind PageRank is to determine the importance of a Web page in terms of the importance assigned to the pages hyperlinking to it. In fact, this thesis is not new, and has been previously successfully exploited in different contexts. We review the PageRank method and link it to some renowned previous techniques that we have found in the fields of Web information retrieval, bibliometrics, sociometry, and econometrics.

arXiv comments
Journal reference
DOI
Subjects
cs.IRInformation Retrieval cs.DLDigital Libraries

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Linked by 3 identifiable commenters in 3 comments across 3 threads, from May 2014 to Jun 2023. Found in 2 HN submissions from Feb 2010 to Oct 2020. Open submission discussions.

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Discussed in comments3 threads

  1. My total comp for creating GitHub Copilot 1 comment

    • Why is this getting aggressively downvoted? Ironically, there's literally a 2010 math paper entitled "PageRank: Standing on the shoulders of giants[1]." [1] https://arxiv.org/pdf/1002.2858.pdf

      dvtView on HNParent context

  2. Google's PageRank patent has expired (2019) 1 comment

    • I was thinking of the Pinski-Narin method, but there are other earlier uses of eigenvector calculations over very similar data: https://arxiv.org/pdf/1002.2858.pdf

      aneilView on HNParent context

  3. The Italian Man Who Inspired Google Web Search 1 comment

    • Massimo Franceschet's 2010 paper "PageRank: Standing on the shoulders of giants" lists some fascinating historical precursors to PageRank.[0][1][2] [0] http://arxiv.org/pdf/1002.2858v3.pdf (pdf) [1] http://arxiv.org/abs/1002.2858 (arxiv) [2]…

      jkldotioView on HNParent context

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