Google's PageRank and Beyond by Amy N. Langville

£28.00
Available
Product Ref. (e.g. ISBN, SKU)
9780691152660
Published:
09 Mar 2012
Format:
Paperback
Number of pages:
224 pages
Dimensions:
254x177.8x14mm
Weight:
0.502kgs
This title is accessible to both the curious reader and the technical computational reader, with each chapter containing something for both audiences. The authors include entertaining asides about such topics as how search engines make money and how the Great Firewall fo China influences research.

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

About the Author: 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.

More Information
Number of pages 224

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