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

by
Amy N. Langville (Author)
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Amy N. Langville (Author),
Carl D. Meyer (Author)
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Carl D. Meyer (Author)
4.1 out of 5 stars 17 customer reviews
ISBN-13: 978-0691122021
ISBN-10: 0691122024
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Product Details

  • Hardcover: 240 pages
  • Publisher: Princeton University Press (July 23, 2006)
  • Language: English
  • ISBN-10: 0691122024
  • ISBN-13: 978-0691122021
  • Product Dimensions: 10 x 7.4 x 0.8 inches
  • Shipping Weight: 8 ounces
  • Average Customer Review: 4.1 out of 5 stars  See all reviews (17 customer reviews)
  • Amazon Best Sellers Rank: #419,694 in Books (See Top 100 in Books)

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Customer Reviews

Top Customer Reviews

5.0 out of 5 starssurveys search techniques
By W Boudville HALL OF FAMEVINE VOICE on August 16, 2006
Format: Hardcover
Langville and Meyer have done a superb job describing both Google's technical foundations, and the broader subject of how search engines rank pages. Over half the book is devoted to explaining the maths and rationales behind PageRank. The level of maths is understandable to those who have done some university level courses on linear algebra (i.e. matrices).

The book also has considerable value in analysing what other organisations (like search engines) and researchers have cobbled together. It gives a useful summation of the state of the research, circa 2006. Essentially, everyone seems to focus on link analysis, after Google revolutionised the industry in 1998 by using this. It blew away the previous leader, AltaVista.

It is true, as the authors point out, that most of the material here has already been published. But as discrete events, scattered through various scientific journals and websites. You can certainly get explanations of PageRank on several websites. But the mathematical depth and reliability of those discussions can vary with the site. The book is far handier.

It is a good starting point, if you are interesting in devising your own search methods.
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5.0 out of 5 starspractical and fun
By jim on January 18, 2007
Format: Hardcover
Great work! I wish I read it before I start my Ph.D. study.

Pros:

1) Precise and intuitive description of the search algorithm

2) Plenty of interesting stories making mathematics fully applicable in practice

3) Sample Matlab code available

Cons:

This is actually a perfect book. But one needs to have basic linear algebra to appreciate its value. If you are looking for "SEO", you are in a wrong spot.

But if anyone wonder how Page and Brin turn math into treasure, read it!
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5.0 out of 5 starsProbability Transition Matrix, Markov Chain, and Stationary Vector
By Man Kam Tam on December 8, 2008
Format: Hardcover
A web search engine has six major components. The components are (1) crawler module, (2) page repository, (3) indexing module, (4) indexes, (5) query module, and (6) ranking module. The ranking module takes the set of relevant pages and ranks them according to both the content score and the popularity score. The popularity score is the focus of Amy N. Langville and Carl D. Meyer's "Google's PageRank and Beyond: The Science of Search Engine Rankings." The popularity score of a web page is determined by Web pages' hyperlink structure.

Brin and Page`s PagerRank philosophy is that a page with more recommendations must be more important than a page with a few links. Or a web page is more important if it is pointed to by other important page. Brin and Page then build a normalized hyperlink matrix (H). With the adjustments named stochasticity and primitivity, a Google matrix (G) is obtained, which is, in fact, a probability transition matrix of a Markov chain. The desired ranking of the web pages is the stationary vector of the matrix G or the solution of the corresponding linear homogeneous system.

To calculate the ranking vector is not an easy task, for the matrix G has 8.1 billion rows and 8.1 billions columns. The matrix is growing everyday as the number of web pages grows everyday. The book consider several major large-scale implementation issues such as storage, convergence criterion, accuracy, dangling nodes, and back button modeling. Accelerating methods are presented as well. They are the adaptive power method, extrapolation, and aggregation. Once the ranking vector is calculated, it has to be updated periodically. However, there is no effective and efficient update method available other than calculating from scratch.Read more ›
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3.0 out of 5 starsThe maths of google
By Carl Cerecke on September 24, 2007
Format: Hardcover
The subtitle "The science of search engine rankings" is a misnomer. This book is primarily about the *mathematics* of pagerank. For non-mathematicians, such as a computer scientist like myself (though I do have undergrad maths), it was pretty slow going and just plain boring.

I wanted algorithm examples for pagerank calculation of largish (10M) data sets. Not matlab code. Matlab might be great for people who love matrices and don't mind being locked-in to a proprietary language, but it is hardly a sensible choice for a production implementation of the pagerank algorithm. And an algorithm using matrix manipulation, while it might be mathematically nice, is difficult to implement efficiently without fancy matrix compression tricks (as far as I can tell).

In the end, I discarded the book, and wrote my own shorter, simpler, non-matrix implementation in python, verified it produced the same results, and then rewrote it in C. It is quite fast enough for 10M pages even without any fancy optimisations. Not a matrix in sight. Yay.

For mathematicians, this book might deserve more than 3 stars. For computer scientists though, I wouldn't recommend it.
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5.0 out of 5 starstruly pagerank and beyond
By M. Clements on March 9, 2007
Format: Hardcover
Great book describing the algorithms that made current search engines so useful and popular. The book describes the math behind the pagerank and HITS algorithms, supported by MATLAB code. Wonderfully written!

Do not buy this book if you want to know how to use search engines, only if you want to understand them!
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5.0 out of 5 starsAn excellent introduction into the algorithms and mathematical bases underlying Pagerank and other link-based algorithms
By HonestAbe on July 21, 2007
Format: Hardcover Verified Purchase
The authors subdivide the book into two main sections: the first few chapters, which are conversational in the manner in which they address pagerank and similar algorithms, and the subsequent chapters, which grow increasingly mathematical. Both authors have strong backgrounds in mathematics, hence that focus. Understanding that, the book is very approachable, lucid and useful in understanding the treated subject matter.
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Most Recent Customer Reviews

3.0 out of 5 starsFor Serious Math Geeks ONly

This book is for very serious mathematicians only. It is highly technical in nature, filled with complex formulas. Difficult to move through

Published on November 22, 2013 by John K. Mauney Jr
4.0 out of 5 starsGood

i am working on page summarisation and i actually needed a mathematical graph method to apply and this book worked.
I like the aside. Read more

Published on August 3, 2013 by Theresa Omodunbi
5.0 out of 5 starsThe first author on this book is Amy, not Carl.

yet the 'short summaries' that (sp)Amazon brings up when listing this book as a recommendation or offering to let you review it lists the *male* SECOND author as the SOLE author. Read more

Published on May 17, 2011 by Cheryl Fillekes
4.0 out of 5 starsGoogle's PageRank and Beyond: The Science of Search Engine Rankings

The book is good at explaining the Google's pageRanking, and it try to present rigorious math proof to demonstrate the idea. Read more

Published on February 16, 2009 by Xin Chen
5.0 out of 5 starsGreat book...

Great book. It's nice to have all the recent work done in trust metrics all in one place.

Published on May 6, 2008 by Kevin A. Burton
4.0 out of 5 starsGood balance

The book strikes a good balance between the novice and the highly experienced math junkie

Published on February 23, 2008 by M. Grant
2.0 out of 5 starsMore a math textbook than anything else

You need a degree in math to comprehend this book - if that is what you are looking for great. If not this book is not for web professionals like myself.

Published on October 29, 2007 by Denise Magic
4.0 out of 5 starsGood review

This book is a good review of the mathematics behind PageRank and other algorithms, such as HITS. It can be used as an auxilliary text in bth graduate and undergraduate... Read more

Published on May 7, 2007 by Geraldo XEXEO
3.0 out of 5 starsA bit dissapoited

I've read Langville's papers as part of my study on link-based ranking techniques. However, the book is only intended to be a very gentle introduction for people with good maths... Read more

Published on March 25, 2007 by Truyen Tran
5.0 out of 5 starsGoogle's PageRank and Beyond

"Google's PageRank and Beyond: The Science of Search Engine Rankings" by Amy N. Langville and Carl D. Meyer is a foremost book presenting the captivating mystery of Google. Read more

Published on March 11, 2007 by Semyon Berkovich

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