Bibliograph

Google's PageRank and beyond, the science of search engine rankings, Amy N. Langville and Carl D. Meyer

Type

Label

Google's PageRank and beyond, the science of search engine rankings, Amy N. Langville and Carl D. Meyer

Language

eng

Bibliography note

Includes bibliographical references (pages [207]-217) and index

Illustrations

illustrations

Index

index present

Literary Form

non fiction

Main title

Google's PageRank and beyond

Nature of contents

bibliography

Oclc number

70663456

Responsibility statement

Amy N. Langville and Carl D. Meyer

Sub title

the science of search engine rankings

Summary

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. --, Provided by Publisher

Table Of Contents

Introduction to web search engines -- Crawling, indexing, and query processing -- Ranking webpages by popularity -- The mathematics of Google's PageRank -- Parameters in the PageRank model -- The sensitivity of PageRank -- The PageRank problem as a linear system -- Issues in large-scale implementation of PageRank -- Accelerating the computation of PageRank -- Updating the PageRank vector -- The HITS method for ranking webpages -- Other link methods for ranking webpages -- The future of web information retrieval -- Resources for web information retrieval -- The mathematics guide

resource.variantTitle

Science of search engine rankingsGoogle page rank and beyondGoogle's page rank and beyondPageRank and beyond

Contributor