Community Structure of Complex Networks (Record no. 13573)

MARC details
000 -LEADER
fixed length control field 02203nmm a22002415i 4500
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20230705150626.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 130107s2013 gw | s |||| 0|eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9783642318214
-- 978-3-642-31821-4
082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 006.312
Edition number 23
100 ## - MAIN ENTRY--PERSONAL NAME
Personal name Shen, Hua-Wei.
9 (RLIN) 19814
245 ## - TITLE STATEMENT
Title Community Structure of Complex Networks
Medium [electronic resource] /
Statement of responsibility, etc. by Hua-Wei Shen.
250 ## - EDITION STATEMENT
Edition statement 1st ed. 2013.
260 ## - PUBLICATION, DISTRIBUTION, ETC.
Place of publication, distribution, etc. Berlin, Heidelberg :
Name of publisher, distributor, etc. Springer Berlin Heidelberg :
-- Imprint: Springer,
Date of publication, distribution, etc. 2013.
300 ## - PHYSICAL DESCRIPTION
Extent XIV, 117 p.
Other physical details online resource.
505 ## - FORMATTED CONTENTS NOTE
Formatted contents note 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 ## - SUMMARY, ETC.
Summary, etc. 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 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Data mining.
9 (RLIN) 19815
Topical term or geographic name entry element StatisticsĀ .
9 (RLIN) 19816
Topical term or geographic name entry element Data Mining and Knowledge Discovery.
9 (RLIN) 19817
Topical term or geographic name entry element Statistics.
9 (RLIN) 19816
856 ## - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier <a href="https://doi.org/10.1007/978-3-642-31821-4">https://doi.org/10.1007/978-3-642-31821-4</a>
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type e-Book
Holdings
Withdrawn status Lost status Source of classification or shelving scheme Damaged status Not for loan Home library Current library Shelving location Date acquired Source of acquisition Total Checkouts Full call number Barcode Date last seen Price effective from Koha item type
    Dewey Decimal Classification     S. R. Ranganathan Learning Hub S. R. Ranganathan Learning Hub Online 2023-07-05 Infokart India Pvt. Ltd., New Delhi   006.312 EB1328 2023-07-05 2023-07-05 e-Book