Google's PageRank and beyond: the science of search engine rankings
Saved in:
| Main Authors: | , |
|---|---|
| Format: | Book |
| Language: | English |
| Published: |
Princeton [u.a.]
Princeton Univ. Press
2006
|
| Subjects: | |
| Online Access: | Inhaltsverzeichnis |
| Item Description: | Hier auch später erschienene, unveränderter Nachdrucke. |
| Physical Description: | X, 224 Seiten Illustrationen |
| ISBN: | 9780691122021 0691122024 9780691152660 |
Staff View
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Record in the Search Index
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|---|---|
| adam_text | Contents
Preface
ix
Chapter
1.
Introduction to Web Search Engines 1
1.1
A Short History of Information Retrieval 1
1.2
An Overview of Traditional Information Retrieval
5
1.3
Web Information Retrieval
9
Chapter
2.
Crawling, Indexing, and Query Processing
15
2.1
Crawling
15
2.2
The Content Index
19
2.3
Query Processing
21
Chapter
3.
Ranking Webpages by Popularity
25
3.1
The Scene in
1998 25
3.2
Two Theses
26
3.3
Query-Independence
30
Chapter
4.
The Mathematics of Google s PageRank
31
4.1
The Original Summation Formula for PageRank
32
4.2
Matrix Representation of the Summation Equations
33
4.3
Problems with the Iterative Process
34
4.4
A Little Markov Chain Theory
36
4.5
Early Adjustments to the Basic Model
З6
4.6
Computation of the PageRank Vector
39
4.7
Theorem and Proof for Spectrum of the Google Matrix
45
Chapter
5.
Parameters in the PageRank Model
47
5.1
The
а
Factor
47
5.2
The Hyperlink Matrix
H
48
5.3
The
Teleportation
Matrix
E
49
Chapter
6.
The Sensitivity of PageRank
57
6.1
Sensitivity with respect to
α
57
Vi
CONTENTS
6.2
Sensitivity with respect to
H
62
6.3
Sensitivity with respect to vT
63
6.4
Other Analyses of Sensitivity
63
6.5
Sensitivity Theorems and Proofs
66
Chapter
7.
The PageRank Problem as a Linear System
71
7.1
Properties of (I
-
aS)
71
7.2
Properties Of (I
-
ttH)
72
7.3
Proof of the PageRank Sparse Linear System
73
Chapter
8.
Issues in Large-Scale Implementation of PageRank
75
8.1
Storage Issues
75
8.2
Convergence Criterion
79
8.3
Accuracy
79
8.4
Dangling Nodes
80
8.5
Back Button Modeling
84
Chapter
9.
Accelerating the Computation of PageRank
89
9.1
An Adaptive Power Method
89
9.2
Extrapolation
90
9.3
Aggregation
94
9.4
Other Numerical Methods
97
Chapter
10.
Updating the PageRank Vector
99
10.1
The Two Updating Problems and their History
100
10.2
Restarting the Power Method
101
10.3
Approximate Updating Using Approximate Aggregation
102
10.4
Exact Aggregation
Ю4
10.5
Exact vs. Approximate Aggregation
105
10.6
Updating with Iterative Aggregation
107
10.7
Determining the Partition
109
10.8
Conclusions
111
Chapter
11.
The HITS Method for Ranking Webpages
115
11.1
The HITS Algorithm
115
11.2
HITS Implementation
117
11.3
HITS Convergence
119
11.4
HITS Example
120
11.5
Strengths and Weaknesses of HITS
122
11.6
HITS s Relationship to Bibliometrics
123
11.7
Query-Independent HITS
124
11.8
Accelerating HITS
126
11.9
HITS Sensitivity
126
CONTENTS
Vii
Chapter
12.
Other Link Methods for Ranking
Webpages
131
12.1
SALSA
131
12.2
Hybrid Ranking Methods
135
12.3
Rankings based on Traffic Flow
1З6
Chapter
13.
The Future of Web Information Retrieval
139
13.1
Spam
139
13.2
Personalization
142
13.3
Clustering
142
13.4
Intelligent Agents
143
13.5
Trends and Time-Sensitive Search
144
13.6
Privacy and Censorship
146
13.7
Library Classification Schemes
147
13.8
Data Fusion
148
Chapter
14.
Resources for Web Information Retrieval
149
14.1
Resources for Getting Started
149
14.2
Resources for Serious Study
150
153
153
167
175
186
192
194
195
198
201
207
219
Chapter
15.
The Mathematics Guide
15.1
Linear Algebra
15.2
Perron-Frobenius Theory
15.3
Markov Chains
15.4
Perron Complementation
15.5
Stochastic Complementation
15.6
Censoring
15.7
Aggregation
15.8
Disaggregation
Chapter
16.
Glossary
Bibliography
Index
|
| adam_txt |
Contents
Preface
ix
Chapter
1.
Introduction to Web Search Engines 1
1.1
A Short History of Information Retrieval 1
1.2
An Overview of Traditional Information Retrieval
5
1.3
Web Information Retrieval
9
Chapter
2.
Crawling, Indexing, and Query Processing
15
2.1
Crawling
15
2.2
The Content Index
19
2.3
Query Processing
21
Chapter
3.
Ranking Webpages by Popularity
25
3.1
The Scene in
1998 25
3.2
Two Theses
26
3.3
Query-Independence
30
Chapter
4.
The Mathematics of Google's PageRank
31
4.1
The Original Summation Formula for PageRank
32
4.2
Matrix Representation of the Summation Equations
33
4.3
Problems with the Iterative Process
34
4.4
A Little Markov Chain Theory
36
4.5
Early Adjustments to the Basic Model
З6
4.6
Computation of the PageRank Vector
39
4.7
Theorem and Proof for Spectrum of the Google Matrix
45
Chapter
5.
Parameters in the PageRank Model
47
5.1
The
а
Factor
47
5.2
The Hyperlink Matrix
H
48
5.3
The
Teleportation
Matrix
E
49
Chapter
6.
The Sensitivity of PageRank
57
6.1
Sensitivity with respect to
α
57
Vi
CONTENTS
6.2
Sensitivity with respect to
H
62
6.3
Sensitivity with respect to vT
63
6.4
Other Analyses of Sensitivity
63
6.5
Sensitivity Theorems and Proofs
66
Chapter
7.
The PageRank Problem as a Linear System
71
7.1
Properties of (I
-
aS)
71
7.2
Properties Of (I
-
ttH)
72
7.3
Proof of the PageRank Sparse Linear System
73
Chapter
8.
Issues in Large-Scale Implementation of PageRank
75
8.1
Storage Issues
75
8.2
Convergence Criterion
79
8.3
Accuracy
79
8.4
Dangling Nodes
80
8.5
Back Button Modeling
84
Chapter
9.
Accelerating the Computation of PageRank
89
9.1
An Adaptive Power Method
89
9.2
Extrapolation
90
9.3
Aggregation
94
9.4
Other Numerical Methods
97
Chapter
10.
Updating the PageRank Vector
99
10.1
The Two Updating Problems and their History
100
10.2
Restarting the Power Method
101
10.3
Approximate Updating Using Approximate Aggregation
102
10.4
Exact Aggregation
Ю4
10.5
Exact vs. Approximate Aggregation
105
10.6
Updating with Iterative Aggregation
107
10.7
Determining the Partition
109
10.8
Conclusions
111
Chapter
11.
The HITS Method for Ranking Webpages
115
11.1
The HITS Algorithm
115
11.2
HITS Implementation
117
11.3
HITS Convergence
119
11.4
HITS Example
120
11.5
Strengths and Weaknesses of HITS
122
11.6
HITS's Relationship to Bibliometrics
123
11.7
Query-Independent HITS
124
11.8
Accelerating HITS
126
11.9
HITS Sensitivity
126
CONTENTS
Vii
Chapter
12.
Other Link Methods for Ranking
Webpages
131
12.1
SALSA
131
12.2
Hybrid Ranking Methods
135
12.3
Rankings based on Traffic Flow
1З6
Chapter
13.
The Future of Web Information Retrieval
139
13.1
Spam
139
13.2
Personalization
142
13.3
Clustering
142
13.4
Intelligent Agents
143
13.5
Trends and Time-Sensitive Search
144
13.6
Privacy and Censorship
146
13.7
Library Classification Schemes
147
13.8
Data Fusion
148
Chapter
14.
Resources for Web Information Retrieval
149
14.1
Resources for Getting Started
149
14.2
Resources for Serious Study
150
153
153
167
175
186
192
194
195
198
201
207
219
Chapter
15.
The Mathematics Guide
15.1
Linear Algebra
15.2
Perron-Frobenius Theory
15.3
Markov Chains
15.4
Perron Complementation
15.5
Stochastic Complementation
15.6
Censoring
15.7
Aggregation
15.8
Disaggregation
Chapter
16.
Glossary
Bibliography
Index |
| any_adam_object | 1 |
| any_adam_object_boolean | 1 |
| author | Langville, Amy N. Meyer, Carl D. |
| author_GND | (DE-588)1029624828 (DE-588)113662262 |
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| author_role | aut aut |
| author_sort | Langville, Amy N. |
| author_variant | a n l an anl c d m cd cdm |
| building | Verbundindex |
| bvnumber | BV021772103 |
| classification_rvk | SK 220 ST 205 |
| ctrlnum | (OCoLC)237198302 (DE-599)BVBBV021772103 |
| discipline | Informatik Mathematik |
| discipline_str_mv | Informatik Mathematik |
| format | Book |
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| publisher | Princeton Univ. Press |
| record_format | marc |
| spelling | Langville, Amy N. Verfasser (DE-588)1029624828 aut Google's PageRank and beyond the science of search engine rankings Amy N. Langville and Carl D. Meyer Princeton [u.a.] Princeton Univ. Press 2006 X, 224 Seiten Illustrationen txt rdacontent n rdamedia nc rdacarrier Hier auch später erschienene, unveränderter Nachdrucke. Mathematik Internet searching Mathematics Web search engines Web sites Ratings Mathematics World Wide Web Subject access Mathematics Suchmaschine (DE-588)4423007-2 gnd rswk-swf Web-Seite (DE-588)4356308-9 gnd rswk-swf Google (DE-588)4726597-8 gnd rswk-swf Rangstatistik (DE-588)4176945-4 gnd rswk-swf Ranking (DE-588)4307945-3 gnd rswk-swf Google (DE-588)4726597-8 s Suchmaschine (DE-588)4423007-2 s Ranking (DE-588)4307945-3 s DE-604 Web-Seite (DE-588)4356308-9 s Rangstatistik (DE-588)4176945-4 s 1\p DE-604 Meyer, Carl D. Verfasser (DE-588)113662262 aut Digitalisierung UB Regensburg application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=014985018&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis 1\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk |
| spellingShingle | Langville, Amy N. Meyer, Carl D. Google's PageRank and beyond the science of search engine rankings Mathematik Internet searching Mathematics Web search engines Web sites Ratings Mathematics World Wide Web Subject access Mathematics Suchmaschine (DE-588)4423007-2 gnd Web-Seite (DE-588)4356308-9 gnd Google (DE-588)4726597-8 gnd Rangstatistik (DE-588)4176945-4 gnd Ranking (DE-588)4307945-3 gnd |
| subject_GND | (DE-588)4423007-2 (DE-588)4356308-9 (DE-588)4726597-8 (DE-588)4176945-4 (DE-588)4307945-3 |
| title | Google's PageRank and beyond the science of search engine rankings |
| title_auth | Google's PageRank and beyond the science of search engine rankings |
| title_exact_search | Google's PageRank and beyond the science of search engine rankings |
| title_exact_search_txtP | Google's PageRank and beyond the science of search engine rankings |
| title_full | Google's PageRank and beyond the science of search engine rankings Amy N. Langville and Carl D. Meyer |
| title_fullStr | Google's PageRank and beyond the science of search engine rankings Amy N. Langville and Carl D. Meyer |
| title_full_unstemmed | Google's PageRank and beyond the science of search engine rankings Amy N. Langville and Carl D. Meyer |
| title_short | Google's PageRank and beyond |
| title_sort | google s pagerank and beyond the science of search engine rankings |
| title_sub | the science of search engine rankings |
| topic | Google Mathematik Internet searching Mathematics Web search engines Web sites Ratings Mathematics World Wide Web Subject access Mathematics Suchmaschine (DE-588)4423007-2 gnd Web-Seite (DE-588)4356308-9 gnd Google (DE-588)4726597-8 gnd Rangstatistik (DE-588)4176945-4 gnd Ranking (DE-588)4307945-3 gnd |
| topic_facet | Google Mathematik Internet searching Mathematics Web search engines Web sites Ratings Mathematics World Wide Web Subject access Mathematics Suchmaschine Web-Seite Rangstatistik Ranking |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=014985018&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| work_keys_str_mv | AT langvilleamyn googlespagerankandbeyondthescienceofsearchenginerankings AT meyercarld googlespagerankandbeyondthescienceofsearchenginerankings |