| 000 -LEADER |
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| fixed length control field |
07911nam a2200853 i 4500 |
| 001 - CONTROL NUMBER |
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| control field |
6813509 |
| 003 - CONTROL NUMBER IDENTIFIER |
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| control field |
IEEE |
| 005 - DATE AND TIME OF LATEST TRANSACTION |
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| control field |
20200413152907.0 |
| 007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION |
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cr cn |||m|||a |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
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| fixed length control field |
121120s2012 caua foab 000 0 eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
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| International Standard Book Number |
9781608451166 (electronic bk.) |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
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| Canceled/invalid ISBN |
9781608451159 (pbk.) |
| 024 7# - OTHER STANDARD IDENTIFIER |
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| Standard number or code |
10.2200/S00449ED1V01Y201209DMK006 |
| Source of number or code |
doi |
| 035 ## - SYSTEM CONTROL NUMBER |
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| System control number |
(OCoLC)814409029 |
| 035 ## - SYSTEM CONTROL NUMBER |
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| System control number |
(CaBNVSL)swl00401681 |
| 040 ## - CATALOGING SOURCE |
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| Original cataloging agency |
CaBNVSL |
| Transcribing agency |
CaBNVSL |
| Modifying agency |
CaBNVSL |
| 050 #4 - LIBRARY OF CONGRESS CALL NUMBER |
|---|
| Classification number |
QA76.9.D343 |
| Item number |
C424 2012 |
| 082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER |
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| Classification number |
006.3 |
| Edition number |
23 |
| 100 1# - MAIN ENTRY--PERSONAL NAME |
|---|
| Personal name |
Chakrabarti, Deepayan. |
| 245 10 - TITLE STATEMENT |
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| Title |
Graph mining |
| Medium |
[electronic resource] : |
| Remainder of title |
laws, tools, and case studies / |
| Statement of responsibility, etc. |
D. Chakrabarti, C. Faloutsos. |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. |
|---|
| Place of publication, distribution, etc. |
San Rafael, Calif. (1537 Fourth Street, San Rafael, CA 94901 USA) : |
| Name of publisher, distributor, etc. |
Morgan & Claypool, |
| Date of publication, distribution, etc. |
c2012. |
| 300 ## - PHYSICAL DESCRIPTION |
|---|
| Extent |
1 electronic text (xv, 191 p.) : |
| Other physical details |
ill., digital file. |
| 490 1# - SERIES STATEMENT |
|---|
| Series statement |
Synthesis lectures on data mining and knowledge discovery, |
| International Standard Serial Number |
2151-0075 ; |
| Volume/sequential designation |
# 6 |
| 538 ## - SYSTEM DETAILS NOTE |
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| System details note |
Mode of access: World Wide Web. |
| 538 ## - SYSTEM DETAILS NOTE |
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| System details note |
System requirements: Adobe Acrobat Reader. |
| 500 ## - GENERAL NOTE |
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| General note |
Part of: Synthesis digital library of engineering and computer science. |
| 500 ## - GENERAL NOTE |
|---|
| General note |
Series from website. |
| 504 ## - BIBLIOGRAPHY, ETC. NOTE |
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| Bibliography, etc. note |
Includes bibliographical references (p. 167-190). |
| 505 0# - FORMATTED CONTENTS NOTE |
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| Formatted contents note |
Acknowledgments -- 1. Introduction -- |
| 505 8# - FORMATTED CONTENTS NOTE |
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| Formatted contents note |
Part I. Patterns and laws -- 2. Patterns in static graphs -- 2.1 S-1: heavy-tailed degree distribution -- 2.2 S-2: Eigenvalue power law (EPL) -- 2.3 S-3 small diameter -- 2.4 S-4, S-5: triangle power laws (TPL, DTPL) -- |
| 505 8# - FORMATTED CONTENTS NOTE |
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| Formatted contents note |
3. Patterns in evolving graphs -- 3.1 D-1: shrinking diameters -- 3.2 D-2: densification power law (DPL) -- 3.3 D-3: diameter-plot and gelling point -- 3.4 D-4: oscillating NLCCs sizes -- 3.5 D-5: LPL, principal Eigenvalue over time -- |
| 505 8# - FORMATTED CONTENTS NOTE |
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| Formatted contents note |
4. Patterns in weighted graphs -- 4.1 W-1: snapshot power laws (SPL) "fortification" -- 4.2 DW-1: weight power law (WPL) -- 4.3 DW-2: LWPL, weighted principal Eigenvalue over time -- |
| 505 8# - FORMATTED CONTENTS NOTE |
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| Formatted contents note |
5. Discussion, the structure of specific graphs -- 5.1 The internet -- 5.2 The World Wide Web (WWW) -- |
| 505 8# - FORMATTED CONTENTS NOTE |
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| Formatted contents note |
6. Discussion, power laws and deviations -- 6.1 Power Laws, slope estimation -- 6.2 Deviations from power laws -- 6.2.1 Exponential cutoffs -- 6.2.2 Lognormals or the "DGX" distribution -- 6.2.3 Doubly-Pareto lognormal (dPln) -- |
| 505 8# - FORMATTED CONTENTS NOTE |
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| Formatted contents note |
7. Summary of patterns -- |
| 505 8# - FORMATTED CONTENTS NOTE |
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| Formatted contents note |
Part II. Graph generators -- 8. Graph generators -- 8.1 Random graph models -- 8.1.1 The Erdös-Rényi random graph model -- 8.1.2 Generalized random graph models -- |
| 505 8# - FORMATTED CONTENTS NOTE |
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| Formatted contents note |
9. Preferential attachment and variants -- 9.1 Main ideas -- 9.1.1 Basic preferential attachment -- 9.1.2 Initial attractiveness -- 9.1.3 Internal edges and rewiring -- 9.2 Related methods -- 9.2.1 Edge copying models -- 9.2.2 Modifying the preferential attachment equation -- 9.2.3 Modeling increasing average degree -- 9.2.4 Node fitness measures -- 9.2.5 Generalizing preferential attachment -- 9.2.6 Pagerank-based preferential attachment -- 9.2.7 The forest fire model -- 9.3 Summary of preferential attachment models -- |
| 505 8# - FORMATTED CONTENTS NOTE |
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| Formatted contents note |
10. Incorporating geographical information -- 10.1 Early models -- 10.1.1 The small-world model -- 10.1.2 The Waxman model -- 10.1.3 The BRITE generator -- 10.1.4 Other geographical constraints -- 10.2 Topology from resource optimizations -- 10.2.1 The highly optimized tolerance model -- 10.2.2 The heuristically optimized tradeoffs model -- 10.3 Generators for the internet topology -- 10.3.1 Structural generators -- 10.3.2 The Inet topology generator -- 10.4 Comparison studies -- |
| 505 8# - FORMATTED CONTENTS NOTE |
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| Formatted contents note |
11. The RMAT (recursive MATrix) graph generator -- |
| 505 8# - FORMATTED CONTENTS NOTE |
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| Formatted contents note |
12. Graph generation by Kronecker multiplication -- |
| 505 8# - FORMATTED CONTENTS NOTE |
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| Formatted contents note |
13. Summary and practitioner's guide -- |
| 505 8# - FORMATTED CONTENTS NOTE |
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| Formatted contents note |
Part III. Tools and case studies -- 14. SVD, random walks, and tensors -- 14.1 Eigenvalues, definition and intuition -- 14.2 Singular value decomposition (SVD) -- 14.3 HITS: hubs and authorities -- 14.4 PageRank -- |
| 505 8# - FORMATTED CONTENTS NOTE |
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| Formatted contents note |
15. Tensors -- 15.1 Introduction -- 15.2 Main ideas -- 15.3 An example: tensors at work -- 15.4 Conclusions, practitioner's guide -- |
| 505 8# - FORMATTED CONTENTS NOTE |
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| Formatted contents note |
16. Community detection -- 16.1 Clustering coefficient -- 16.2 Methods for extracting graph communities -- 16.3 A word of caution "no good cuts" -- |
| 505 8# - FORMATTED CONTENTS NOTE |
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| Formatted contents note |
17. Influence/virus propagation and immunization -- 17.1 Introduction, terminology -- 17.2 Main result and its generality -- 17.3 Applications -- 17.4 Discussion -- 17.4.1 Simulation examples -- 17.4.2 Measure of connectivity -- 17.5 Conclusion -- |
| 505 8# - FORMATTED CONTENTS NOTE |
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| Formatted contents note |
18. Case studies -- 18.1 Proximity and random walks -- 18.2 Automatic captioning, multi-modal querying -- 18.2.1 The GCap method -- 18.2.2 Performance and variations -- 18.2.3 Discussion -- 18.2.4 Conclusions -- 18.3 Center-piece subgraphs, who is the mastermind? -- |
| 505 8# - FORMATTED CONTENTS NOTE |
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| Formatted contents note |
Part IV. Outreach, related work -- 19. Social networks -- 19.1 Mapping social networks -- 19.2 Dataset characteristics -- 19.3 Structure from data -- 19.4 Social "roles" -- 19.5 Social capital -- 19.6 Recent research directions -- 19.7 Differences from graph mining -- |
| 505 8# - FORMATTED CONTENTS NOTE |
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| Formatted contents note |
20. Other related work -- 20.1 Relational learning -- 20.2 Finding frequent subgraphs -- 20.3 Navigation in graphs -- 20.3.1 Methods of navigation -- 20.3.2 Relationship between graph topology and ease of navigation -- 20.4 Using social networks in other fields -- |
| 505 8# - FORMATTED CONTENTS NOTE |
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| Formatted contents note |
21. Conclusions -- 21.1 Future research directions -- 21.2 Parting thoughts -- |
| 505 8# - FORMATTED CONTENTS NOTE |
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| Formatted contents note |
Resources -- Bibliography -- Authors' biographies. |
| 506 1# - RESTRICTIONS ON ACCESS NOTE |
|---|
| Terms governing access |
Abstract freely available; full-text restricted to subscribers or individual document purchasers. |
| 510 0# - CITATION/REFERENCES NOTE |
|---|
| Name of source |
Compendex |
| 510 0# - CITATION/REFERENCES NOTE |
|---|
| Name of source |
INSPEC |
| 510 0# - CITATION/REFERENCES NOTE |
|---|
| Name of source |
Google scholar |
| 510 0# - CITATION/REFERENCES NOTE |
|---|
| Name of source |
Google book search |
| 520 3# - SUMMARY, ETC. |
|---|
| Summary, etc. |
What does the Web look like? How can we find patterns, communities, outliers, in a social network? Which are the most central nodes in a network? These are the questions that motivate this work. Networks and graphs appear in many diverse settings, for example in social networks, computer-communication networks (intrusion detection, traffic management), protein-protein interaction networks in biology, document-text bipartite graphs in text retrieval, person-account graphs in financial fraud detection, and others. In this work, first we list several surprising patterns that real graphs tend to follow. Then we give a detailed list of generators that try to mirror these patterns. Generators are important, because they can help with "what if " scenarios, extrapolations, and anonymization. Then we provide a list of powerful tools for graph analysis, and specifically spectral methods (Singular Value Decomposition (SVD)), tensors, and case studies like the famous "pageRank" algorithm and the "HITS" algorithm for ranking web search results. Finally, we conclude with a survey of tools and observations from related fields like sociology, which provide complementary viewpoints. |
| 530 ## - ADDITIONAL PHYSICAL FORM AVAILABLE NOTE |
|---|
| Additional physical form available note |
Also available in print. |
| 588 ## - SOURCE OF DESCRIPTION NOTE |
|---|
| Source of description note |
Title from PDF t.p. (viewed on November 20, 2012). |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Data mining. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Social networks |
| General subdivision |
Mathematical models. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Computer networks |
| General subdivision |
Mathematical models. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Graph theory. |
| 653 ## - INDEX TERM--UNCONTROLLED |
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| Uncontrolled term |
data mining |
| 653 ## - INDEX TERM--UNCONTROLLED |
|---|
| Uncontrolled term |
social networks |
| 653 ## - INDEX TERM--UNCONTROLLED |
|---|
| Uncontrolled term |
power laws |
| 653 ## - INDEX TERM--UNCONTROLLED |
|---|
| Uncontrolled term |
graph generators |
| 653 ## - INDEX TERM--UNCONTROLLED |
|---|
| Uncontrolled term |
pagerank |
| 653 ## - INDEX TERM--UNCONTROLLED |
|---|
| Uncontrolled term |
singular value decomposition |
| 700 1# - ADDED ENTRY--PERSONAL NAME |
|---|
| Personal name |
Faloutsos, Christos. |
| 776 08 - ADDITIONAL PHYSICAL FORM ENTRY |
|---|
| Relationship information |
Print version: |
| International Standard Book Number |
9781608451159 |
| 830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE |
|---|
| Uniform title |
Synthesis digital library of engineering and computer science. |
| 830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE |
|---|
| Uniform title |
Synthesis lectures on data mining and knowledge discovery ; |
| Volume/sequential designation |
# 6. |
| International Standard Serial Number |
2151-0075 |
| 856 42 - ELECTRONIC LOCATION AND ACCESS |
|---|
| Materials specified |
Abstract with links to resource |
| Uniform Resource Identifier |
http://ieeexplore.ieee.org/servlet/opac?bknumber=6813509 |
