Community Structure of Complex Networks - Springer Theses (Paperback)
  • Community Structure of Complex Networks - Springer Theses (Paperback)

Community Structure of Complex Networks - Springer Theses (Paperback)

Paperback 117 Pages / Published: 24/06/2015
  • We can order this from the publisher

Usually dispatched within 15 working days

Important information: this item can only be delivered to a UK address. More information
  • This item has been added to your basket

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.

Publisher: Springer-Verlag Berlin and Heidelberg GmbH & Co. KG
ISBN: 9783642434815
Number of pages: 117
Weight: 2117 g
Dimensions: 235 x 155 x 7 mm
Edition: 2013 ed.


From the book reviews:

"The topic of this book is the analysis of community structures. ... this book provides a unique viewpoint on network analysis. It is a good handbook for engineers specializing in modern network analysis." (Hsun-Hsien Chang, Computing Reviews, June, 2014)

"The monograph offers an exceptional set of methods of research on networks, and can be useful and interesting to researchers and students in various areas." (Stan Lipovetsky, Technometrics, Vol. 30 (1), 2018)

You may also be interested in...

Data Analysis Using SQL and Excel
Added to basket
Mining of Massive Datasets
Added to basket
Data Science for Business
Added to basket
Doing Data Science
Added to basket
The Elements of Statistical Learning
Added to basket
Applied Predictive Analytics
Added to basket

Please sign in to write a review

Your review has been submitted successfully.