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130107s2013 gw | s |||| 0|eng d |
| 020 |
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|a 9783642318214
|9 978-3-642-31821-4
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|a 10.1007/978-3-642-31821-4
|2 doi
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|a QA76.9.D343
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|a 006.312
|2 23
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|a Shen, Hua-Wei.
|e author.
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|a Community Structure of Complex Networks
|c by Hua-Wei Shen.
|h [electronic resource] /
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| 264 |
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|a Berlin, Heidelberg :
|b Springer Berlin Heidelberg :
|b Imprint: Springer,
|c 2013.
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| 300 |
# |
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|a XIV, 120 p. 48 illus., 17 illus. in color.
|b online resource.
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| 336 |
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|a text
|b txt
|2 rdacontent
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| 337 |
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|a computer
|b c
|2 rdamedia
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|a online resource
|b cr
|2 rdacarrier
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| 347 |
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|a text file
|b PDF
|2 rda
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| 490 |
1 |
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|a Springer Theses, Recognizing Outstanding Ph.D. Research,
|x 2190-5053
|
| 505 |
0 |
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|a Community structure: An Introduction -- Detecting the overlapping and hierarchical community structure in networks -- Multiscale community detection in networks with heterogeneous degree distributions -- Community structure and diffusion dynamics on networks -- Exploratory Analysis of the structural regularities in networks.
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| 520 |
# |
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|a Community structure is a salient structural characteristic of many real-world networks. Communities are generally hierarchical, overlapping, multi-scale and coexist with other types of structural regularities of networks. This poses major challenges for conventional methods of community detection. This book will comprehensively introduce the latest advances in community detection, especially the detection of overlapping and hierarchical community structures, the detection of multi-scale communities in heterogeneous networks, and the exploration of multiple types of structural regularities. These advances have been successfully applied to analyze large-scale online social networks, such as Facebook and Twitter. This book provides readers a convenient way to grasp the cutting edge of community detection in complex networks. The thesis on which this book is based was honored with the Top 100 Excellent Doctoral Dissertations Award from the Chinese Academy of Sciences and was nominated as the Outstanding Doctoral Dissertation by the Chinese Computer Federation.
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| 650 |
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|a Computer science.
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| 650 |
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|a Data mining.
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| 650 |
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|a Statistics.
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| 650 |
1 |
4 |
|a Computer Science.
|
| 650 |
2 |
4 |
|a Data Mining and Knowledge Discovery.
|
| 650 |
2 |
4 |
|a Statistics, general.
|
| 710 |
2 |
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|a SpringerLink (Online service)
|
| 773 |
0 |
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|t Springer eBooks
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| 776 |
0 |
8 |
|i Printed edition:
|z 9783642318207
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| 830 |
# |
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|a Springer Theses, Recognizing Outstanding Ph.D. Research,
|x 2190-5053
|
| 856 |
4 |
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|u https://ezaccess.library.uitm.edu.my/login?url=http://dx.doi.org/10.1007/978-3-642-31821-4
|
| 912 |
# |
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|a ZDB-2-SCS
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| 950 |
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|a Computer Science (Springer-11645)
|