Community Structure of Complex Networks

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. T...

Πλήρης περιγραφή

Λεπτομέρειες βιβλιογραφικής εγγραφής
Κύριος συγγραφέας: Shen, Hua-Wei (Συγγραφέας)
Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
Γλώσσα:English
Έκδοση: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2013.
Σειρά:Springer Theses, Recognizing Outstanding Ph.D. Research,
Θέματα:
Διαθέσιμο Online:Full Text via HEAL-Link
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100 1 |a Shen, Hua-Wei.  |e author. 
245 1 0 |a Community Structure of Complex Networks  |h [electronic resource] /  |c by Hua-Wei Shen. 
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300 |a XIV, 117 p.  |b online resource. 
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490 1 |a Springer Theses, Recognizing Outstanding Ph.D. Research,  |x 2190-5053 
505 0 |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. 
520 |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. 
650 0 |a Computer science. 
650 0 |a Data mining. 
650 0 |a Statistics. 
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650 2 4 |a Statistics, general. 
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830 0 |a Springer Theses, Recognizing Outstanding Ph.D. Research,  |x 2190-5053 
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