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Honorable Mention for the 2006 Award for Best Professional/Scholarly Book in Computer & Information Science, Association of American Publishers "[F]or anyone who wants to delve deeply into just how Google's PageRank works, I recommend Google's PageRank and Beyond."--Stephen H. Wildstrom, BusinessWeek "This is a worthwhile book. It offers a comprehensive and erudite presentation of PageRank and related search-engine algorithms, and it is written in an approachable way, given the mathematical foundations involved."--Jonathan Bowen, Times Higher Education Supplement "This book should be at the top of anyone's list as a must-read for those interested in how search engines work and, more specifically how Google is to meet the needs of so many people in so many ways."--Michael W. Berry, SIAM Review "Amy N. Langville and Carl D. Meyer examine the logic, mathematics, and sophistication behind Google's PageRank and other Internet search engine ranking programs... It is an excellent work."--Ian D. Gordon, Library Journal "If I were taking, or teaching, a course in linear algebra today, this book would be a godsend."--Ed Gerstner, Nature Physics "Langville and Meyer present the mathematics in all its detail... But they vary the math with discussions of the many issues involved in building search engines, the 'wars' between search engine developers and those trying to artificially inflate the position of their pages, and the future of search-engine development... Google's PageRank and Beyond makes good reading for anyone, student or professional, who wants to understand the details of search engines."--James Hendler, Physics Today "This book is written for people who are curious about new science and technology as well as for those with more advanced background in matrix theory... Much of the book can be easily followed by general readers, while understanding the remaining part requires only a good first course in linear algebra. It can be a reference book for people who want to know more about the ideas behind the currently popular search engines, and it provides an introductory text for beginning researchers in the area of information retrieval."--Jiu Ding, Mathemathical Reviews "The book is very attractively and clearly written. The authors succeed to manage in an optimal way the presentation of both basic and more sophisticated concepts involved in the analysis of Google's PageRank, such that the book serves both audiences: the general and the technical scientific public."--Constantin Popa, Zentralblatt MATH "The book under review is excellently written, with a fresh and engaging style. The reader will particularly enjoy the 'Asides' interspersed throughout the text. They contain all kind of entertaining stories, practical tips, and amusing quotes... The book also contains some useful resources for computation."--Pablo Fernandez, Mathematical Intelligencer "Google's PageRank and Beyond describes the link analysis tool called PageRank, puts it in the context of web search engines and information retrieval, and describes competing methods for ranking webpages. It is an utterly engaging book."--Bill Satzer, MathDL.maa.orgReseña del editor:
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
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