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020 _a9783540319559
_9978-3-540-31955-9
024 7 _a10.1007/b106453
_2doi
050 4 _aQA76.9.M35
050 4 _aQA297.4
072 7 _aUYAM
_2bicssc
072 7 _aPBD
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072 7 _aCOM014000
_2bisacsh
072 7 _aUYAM
_2thema
072 7 _aPBD
_2thema
082 0 4 _a004.0151
_223
245 1 0 _aNetwork Analysis
_h[electronic resource] :
_bMethodological Foundations /
_cedited by Ulrik Brandes, Thomas Erlebach.
250 _a1st ed. 2005.
264 1 _aBerlin, Heidelberg :
_bSpringer Berlin Heidelberg :
_bImprint: Springer,
_c2005.
300 _aXII, 472 p.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aTheoretical Computer Science and General Issues,
_x2512-2029 ;
_v3418
505 0 _aFundamentals -- I Elements -- Centrality Indices -- Algorithms for Centrality Indices -- Advanced Centrality Concepts -- II Groups -- Local Density -- Connectivity -- Clustering -- Role Assignments -- Blockmodels -- Network Statistics -- Network Comparison -- Network Models -- Spectral Analysis -- Robustness and Resilience.
520 _a‘Network’ is a heavily overloaded term, so that ‘network analysis’ means different things to different people. Specific forms of network analysis are used in the study of diverse structures such as the Internet, interlocking directorates, transportation systems, epidemic spreading, metabolic pathways, the Web graph, electrical circuits, project plans, and so on. There is, however, a broad methodological foundation which is quickly becoming a prerequisite for researchers and practitioners working with network models. From a computer science perspective, network analysis is applied graph theory. Unlike standard graph theory books, the content of this book is organized according to methods for specific levels of analysis (element, group, network) rather than abstract concepts like paths, matchings, or spanning subgraphs. Its topics therefore range from vertex centrality to graph clustering and the evolution of scale-free networks. In 15 coherent chapters, this monograph-like tutorial book introduces and surveys the concepts and methods that drive network analysis, and is thus the first book to do so from a methodological perspective independent of specific application areas.
650 0 _aComputer science
_xMathematics.
650 0 _aDiscrete mathematics.
650 0 _aComputer networks .
650 0 _aArtificial intelligence
_xData processing.
650 0 _aAlgorithms.
650 1 4 _aDiscrete Mathematics in Computer Science.
650 2 4 _aComputer Communication Networks.
650 2 4 _aDiscrete Mathematics.
650 2 4 _aData Science.
650 2 4 _aAlgorithms.
700 1 _aBrandes, Ulrik.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
700 1 _aErlebach, Thomas.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
710 2 _aSpringerLink (Online service)
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783540249795
776 0 8 _iPrinted edition:
_z9783540807872
830 0 _aTheoretical Computer Science and General Issues,
_x2512-2029 ;
_v3418
856 4 0 _uhttps://doi.org/10.1007/b106453
912 _aZDB-2-SCS
912 _aZDB-2-SXCS
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942 _cSPRINGER
999 _c185246
_d185246