Kooperativer Bibliotheksverbund

UID:

Format: X, 224 Seiten : , Illustrationen.

ISBN: 978-0-691-12202-1 , 0-691-12202-4 , 978-0-691-15266-0

Note: Hier auch später erschienene, unveränderter Nachdrucke.

Language: English

Subjects: Computer Science , Mathematics

Keywords: Google ; Suchmaschine ; Ranking ; Google ; Web-Seite ; Rangstatistik

URL: Inhaltsverzeichnis

URL: Inhaltsverzeichnis

URL: Autorenbiografie

URL: Verlagsangaben

URL: Inhaltsverzeichnis

URL: Inhaltstext

Author information: Meyer, Carl D.

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Format: XVI, 247 S. : , Ill., graph. Darst.

ISBN: 978-0-691-15422-0

Note: Includes bibliographical references and index

Language: English

Subjects: General works , Mathematics

Keywords: Ranking ; Statistik ; Methodologie ; Rating

URL: http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=024894299&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA

URL: Inhaltsverzeichnis

URL: http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=024894299&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA

Author information: Meyer, Carl D.

UID:

Format: X, 224 p.

ISBN: 0-691-12202-4 , 978-0-691-12202-1

Note: Includes bibliographical references (p. [207]-217) and index

Language: English

UID:

Format: X, 224 S. : , Ill., graph. Darst.

Edition: Neuaufl.

ISBN: 978-0-691-15266-0 , 0-691-15266-7

Language: English

Subjects: Computer Science , Mathematics

Keywords: Google ; Suchmaschine ; Ranking ; Google ; Web-Seite ; Rangstatistik

Author information: Meyer, Carl D.

UID:

Format: xvi, 247 p. : , ill.

Edition: Electronic reproduction. Ann Arbor, MI : ProQuest, 2015. Available via World Wide Web. Access may be limited to ProQuest affiliated libraries.

Language: English

Keywords: Electronic books.

URL: Click to View

UID:

Format: 1 online resource (235 p.)

Edition: Course Book

ISBN: 1-282-45843-4 , 9786612458439 , 1-4008-3032-X

Content: 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

Note: Description based upon print version of record. , Frontmatter -- , Contents -- , Preface -- , Chapter One. Introduction to Web Search Engines -- , Chapter Two. Crawling, Indexing, and Query Processing -- , Chapter Three. Ranking Webpages by Popularity -- , Chapter Four. The Mathematics of Google's PageRank -- , Chapter Five. Parameters in the PageRank Model -- , Chapter Six. The Sensitivity of PageRank -- , Chapter Seven. The PageRank Problem as a Linear System -- , Chapter Eight. Issues in Large-Scale Implementation of PageRank -- , Chapter Nine. Accelerating the Computation of PageRank -- , Chapter Ten. Updating the PageRank Vector -- , Chapter Eleven. The HITS Method for Ranking Webpages -- , Chapter Twelve. Other Link Methods for Ranking Webpages -- , Chapter Thirteen. The Future of Web Information Retrieval -- , Chapter Fourteen. Resources for Web Information Retrieval -- , Chapter Fifteen. The Mathematics Guide -- , Chapter Sixteen. Glossary -- , Bibliography -- , Index , Issued also in print. , English

Additional Edition: ISBN 0-691-15266-7

Additional Edition: ISBN 0-691-12202-4

Language: English

DOI: 10.1515/9781400830329

UID:

Format: 1 online resource (343 p.)

ISBN: 1-932482-35-0

Content: The Markov Anniversary Meeting, June 12-14, 2006 was the fifth in a series of conferences devoted to the Numerical Solution of Markov Chains (NSMC). The prior four NSMC conferences were held in 1990, 1995, 1999, and 2003. The first two conferences were held in Raleigh, North Carolina, the third moved overseas to Zarazoga, Spain, and the fourth was held in Urbana-Champaign, Illinois. This fifth and most recent Markov meeting occurred sooner than the usual 4-5 year schedule in order to celebrate two very important events: the 150th anniversary of Andrei A. Markov's birth and the 100th anniversar

Note: Description based upon print version of record. , Contents; Preface; Program Committee; 1. Seneta; 2. Burrage et. al.; 3. Cloth and Haverkort; 4. Marie; 5. Latouche; 6. Spaey, Houdt and Blondia; 7. Vuuren and Adan; 8. Tian and Perros; 9. Dopper, Gaujal and Vincent; 10. Horvath and Telek; 11. Hilgers and Langville; 12. Da Silva and Rubino; 13. Mamoun, Busic, Fourneau and Pekergin; 14. Dayar et. al.; 15. Langville and Meyer; 16. Benzi and Ucar; 17. Tancrez and Semal; 18. Kirkland; 19. Dayar; 20. Sbeity and Plateau; 21. Kumar; 22. Caswell , English

Additional Edition: ISBN 1-932482-34-2

Language: English

UID:

Format: 1 online resource (266 p.)

Edition: Course Book

ISBN: 1-4008-4167-4 , 1-283-41176-8 , 9786613411761

Content: A website's ranking on Google can spell the difference between success and failure for a new business. NCAA football ratings determine which schools get to play for the big money in postseason bowl games. Product ratings influence everything from the clothes we wear to the movies we select on Netflix. Ratings and rankings are everywhere, but how exactly do they work? Who's #1? offers an engaging and accessible account of how scientific rating and ranking methods are created and applied to a variety of uses. Amy Langville and Carl Meyer provide the first comprehensive overview of the mathematical algorithms and methods used to rate and rank sports teams, political candidates, products, Web pages, and more. In a series of interesting asides, Langville and Meyer provide fascinating insights into the ingenious contributions of many of the field's pioneers. They survey and compare the different methods employed today, showing why their strengths and weaknesses depend on the underlying goal, and explaining why and when a given method should be considered. Langville and Meyer also describe what can and can't be expected from the most widely used systems. The science of rating and ranking touches virtually every facet of our lives, and now you don't need to be an expert to understand how it really works. Who's #1? is the definitive introduction to the subject. It features easy-to-understand examples and interesting trivia and historical facts, and much of the required mathematics is included.

Note: Description based upon print version of record. , Front matter -- , Contents -- , Preface -- , Chapter 1. Introduction to Ranking -- , Chapter 2. Massey's Method -- , Chapter 3. Colley's Method -- , Chapter 4. Keener's Method -- , Chapter 5. Elo's System -- , Chapter 6. The Markov Method -- , Chapter 7. The Offense-Defense Rating Method -- , Chapter 8. Ranking by Reordering Methods -- , Chapter 9. Point Spreads -- , Chapter 10. User Preference Ratings -- , Chapter 11. Handling Ties -- , Chapter 12. Incorporating Weights -- , Chapter 13. "What If . . ." Scenarios and Sensitivity -- , Chapter 14. Rank Aggregation-Part 1 -- , Chapter 15. Rank Aggregation-Part 2 -- , Chapter 16. Methods of Comparison -- , Chapter 17. Data -- , Chapter 18. Epilogue -- , Glossary -- , Bibliography -- , Index , Issued also in print. , English

Additional Edition: ISBN 0-691-15422-8

Additional Edition: ISBN 0-691-16231-X

Language: English

DOI: 10.1515/9781400841677

UID:

Format: 1 online resource (240 p.) : , 11 halftones. 26 line illus.

Edition: Course Book

ISBN: 9781400830329

Content: 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

Note: Frontmatter -- , Contents -- , Preface -- , Chapter One. Introduction to Web Search Engines -- , Chapter Two. Crawling, Indexing, and Query Processing -- , Chapter Three. Ranking Webpages by Popularity -- , Chapter Four. The Mathematics of Google’s PageRank -- , Chapter Five. Parameters in the PageRank Model -- , Chapter Six. The Sensitivity of PageRank -- , Chapter Seven. The PageRank Problem as a Linear System -- , Chapter Eight. Issues in Large-Scale Implementation of PageRank -- , Chapter Nine. Accelerating the Computation of PageRank -- , Chapter Ten. Updating the PageRank Vector -- , Chapter Eleven. The HITS Method for Ranking Webpages -- , Chapter Twelve. Other Link Methods for Ranking Webpages -- , Chapter Thirteen. The Future of Web Information Retrieval -- , Chapter Fourteen. Resources for Web Information Retrieval -- , Chapter Fifteen. The Mathematics Guide -- , Chapter Sixteen. Glossary -- , Bibliography -- , Index , In English.

Language: English

DOI: 10.1515/9781400830329

URL: https://doi.org/10.1515/9781400830329

URL: https://www.degruyter.com/isbn/9781400830329

URL: https://doi.org/10.1515/9781400830329

URL: https://www.degruyter.com/isbn/9781400830329

UID:

Format: 1 online resource (272 p.) : , 25 halftones. 47 line illus. 60 tables.

Edition: Course Book

ISBN: 9781400841677

Content: A website's ranking on Google can spell the difference between success and failure for a new business. NCAA football ratings determine which schools get to play for the big money in postseason bowl games. Product ratings influence everything from the clothes we wear to the movies we select on Netflix. Ratings and rankings are everywhere, but how exactly do they work? Who's #1? offers an engaging and accessible account of how scientific rating and ranking methods are created and applied to a variety of uses. Amy Langville and Carl Meyer provide the first comprehensive overview of the mathematical algorithms and methods used to rate and rank sports teams, political candidates, products, Web pages, and more. In a series of interesting asides, Langville and Meyer provide fascinating insights into the ingenious contributions of many of the field's pioneers. They survey and compare the different methods employed today, showing why their strengths and weaknesses depend on the underlying goal, and explaining why and when a given method should be considered. Langville and Meyer also describe what can and can't be expected from the most widely used systems. The science of rating and ranking touches virtually every facet of our lives, and now you don't need to be an expert to understand how it really works. Who's #1? is the definitive introduction to the subject. It features easy-to-understand examples and interesting trivia and historical facts, and much of the required mathematics is included.

Note: Frontmatter -- , Contents -- , Preface -- , Chapter 1. Introduction to Ranking -- , Chapter 2. Massey’s Method -- , Chapter 3. Colley’s Method -- , Chapter 4. Keener’s Method -- , Chapter 5. Elo’s System -- , Chapter 6. The Markov Method -- , Chapter 7. The Offense–Defense Rating Method -- , Chapter 8. Ranking by Reordering Methods -- , Chapter 9. Point Spreads -- , Chapter 10. User Preference Ratings -- , Chapter 11. Handling Ties -- , Chapter 12. Incorporating Weights -- , Chapter 13. “What If . . .” Scenarios and Sensitivity -- , Chapter 14. Rank Aggregation–Part 1 -- , Chapter 15. Rank Aggregation–Part 2 -- , Chapter 16. Methods of Comparison -- , Chapter 17. Data -- , Chapter 18. Epilogue -- , Glossary -- , Bibliography -- , Index , In English.

Language: English

DOI: 10.1515/9781400841677

URL: https://doi.org/10.1515/9781400841677

URL: https://www.degruyter.com/isbn/9781400841677

URL: https://doi.org/10.1515/9781400841677

URL: https://www.degruyter.com/isbn/9781400841677