Cited by 814Information Retrieval and Search BehaviorWeb visibility and informetricsWeb Data Mining and Analysis

Google's PageRank and Beyond: The Science of Search Engine Rankings

Langville, Amy N., Meyer, Carl D.·2006·Princeton University Press eBooks

Abstract

Why doesn't your home page appear on the first page of search results, even when you query your own name? How do other web pages always appear at the top? What creates these powerful rankings? And how? The first book ever about the science of web page rankings, Google's PageRank and Beyond supplies the answers to these and other questions and more. The book serves two very different audiences: the curious science reader and the technical computational reader. The chapters build in mathematical sophistication, so that the first five are accessible to the general academic reader. While other chapters are much more mathematical in nature, each one contains something for both audiences. For example, the authors include entertaining asides such as how search engines make money and how the Great Firewall of China influences research. The book includes an extensive background chapter designed to help readers learn more about the mathematics of search engines, and it contains several MATLAB codes and links to sample web data sets. The philosophy throughout is to encourage readers to experiment with the ideas and algorithms in the text. Any business seriously interested in improving its rankings in the major search engines can benefit from the clear examples, sample code, and list of resources provided. Many illustrative examples and entertaining asides MATLAB code Accessible and informal style Complete and self-contained section for mathematics review

Integrity signals

Registry

Crossref · 10.1515/9781400830329

Cites

1 of 1 references verified0 citation errors · 0 not checkable

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  • D is not the same random variable as an out-degree of a random page because the additional information that a page has a link to i alters the out-degree distribution.

    “Note that D is not the same random variable as an out-degree of a random page since the additional information that a page has a link to i alters the out-degree distribution. This phenomenon is known as the inspection paradox [36].”

    From Asymptotic analysis for personalized Web search (2010) · cites this paper as [36]

  • The number of out-links from a page containing a random link is stochastically larger than an out-degree of a random page.

    “Thus, the number of out-links from a page containing a random link is stochastically larger than an out-degree of a random page.”

    From Asymptotic analysis for personalized Web search (2010) · cites this paper as [36]

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Authors
Langville, A. N., & Meyer, C. D.
Venue
Princeton University Press eBooks
Published
2006-12-31
OpenAlex
W2271295020
Cited by
814
References
1
Citations by year
2026: 19 · 2025: 39 · 2024: 35 · 2023: 29 · 2022: 37 · 2021: 29 · 2020: 24 · 2019: 31 · 2018: 41 · 2017: 41 · 2016: 35 · 2015: 44 · 2014: 57 · 2013: 68 · 2012: 61
FWCI
51.62
Type
book
Language
en
Open access
closed
Locations
Princeton University Press eBooks (publishedVersion)
Topics
  • Physical Sciences › Computer Science › Information Systems › Information Retrieval and Search Behavior
  • Physical Sciences › Computer Science › Information Systems › Web visibility and informetrics
  • Physical Sciences › Computer Science › Information Systems › Web Data Mining and Analysis
Keywords
PageRank, web page ranking, search engines, Google, link analysis, ranking algorithms, search engine optimization, Great Firewall of China

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