Grouping Information

Hoopla Extract Information

stdClass Object
(
    [year] => 2011
    [artist] => Amy N. Langville
    [fiction] => 
    [coverImageUrl] => https://cover.hoopladigital.com/pup_9781400830329_270.jpeg
    [titleId] => 13282674
    [isbn] => 9781400830329
    [abridged] => 
    [language] => ENGLISH
    [profanity] => 
    [title] => Google's PageRank and Beyond
    [demo] => 
    [segments] => Array
        (
        )

    [pages] => 240
    [children] => 
    [artists] => Array
        (
            [0] => stdClass Object
                (
                    [name] => Amy N. Langville
                    [artistFormal] => Langville, Amy N.
                    [relationship] => AUTHOR
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            [1] => stdClass Object
                (
                    [name] => Carl D. Meyer
                    [artistFormal] => Meyer, Carl D.
                    [relationship] => AUTHOR
                )

        )

    [genres] => Array
        (
            [0] => Algorithms
            [1] => Computers
            [2] => Internet
            [3] => Mathematics
            [4] => Programming
            [5] => Search Engines
            [6] => Software Development & Engineering
        )

    [price] => 1.49
    [id] => 13282674
    [edited] => 
    [kind] => EBOOK
    [active] => 1
    [upc] => 
    [synopsis] => "Honorable Mention for the 2006 Award for Best Professional/Scholarly Book in Computer & Information Science, Association of American Publishers" Amy N. Langville is Assistant Professor of  Mathematics at the College of Charleston in Charleston, South Carolina. She studies mathematical algorithms for information retrieval and text and data mining applications. Carl D. Meyer is Professor of Mathematics at North Carolina State University. In addition to information retrieval, his research areas include numerical analysis, linear algebra, and Markov chains. He is the author of Matrix Analysis and Applied Linear Algebra. 
	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

 "[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
    [url] => https://www.hoopladigital.com/title/13282674
    [pa] => 
    [subtitle] => The Science of Search Engine Rankings
    [publisher] => Princeton University Press
    [purchaseModel] => INSTANT
)