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001 978-3-642-30287-9
003 DE-He213
005 20140220082848.0
007 cr nn 008mamaa
008 120726s2013 gw | s |||| 0|eng d
020 _a9783642302879
_9978-3-642-30287-9
024 7 _a10.1007/978-3-642-30287-9
_2doi
050 4 _aQ342
072 7 _aUYQ
_2bicssc
072 7 _aCOM004000
_2bisacsh
082 0 4 _a006.3
_223
100 1 _aMenezes, Ronaldo.
_eeditor.
245 1 0 _aComplex Networks
_h[electronic resource] /
_cedited by Ronaldo Menezes, Alexandre Evsukoff, Marta C. González.
264 1 _aBerlin, Heidelberg :
_bSpringer Berlin Heidelberg :
_bImprint: Springer,
_c2013.
300 _aX, 266 p. 85 illus.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aStudies in Computational Intelligence,
_x1860-949X ;
_v424
505 0 _aNetwork Measures and Models -- Agents, Communication and Mobility -- Communities, Clusters and Partitions -- Emergence in Networks -- Social Structures and Networks -- Networks in Biology and Medicine -- Applications of Networks.
520 _aIn the last decade we have seen the emergence of a new inter-disciplinary field focusing on the understanding of networks which are dynamic, large, open, and have a structure sometimes called random-biased. The field of Complex Networks is helping us better understand many complex phenomena such as the spread of  deseases, protein interactions, social relationships, to name but a few. Studies in Complex Networks are gaining attention due to some major scientific breakthroughs proposed by network scientists helping us understand and model interactions contained in large datasets. In fact, if we could point to one event leading to the widespread use of complex network analysis is the availability of online databases. Theories of Random Graphs from Erdös and Rényi from the late 1950s led us to believe that most networks had random characteristics. The work on large online datasets told us otherwise. Starting with the work of Barabási and Albert as well as Watts and Strogatz in the late 1990s, we now know that most real networks are characterized by degree distributions that fit a power law (scale-free networks), and that they are highly clustered with small average path lengths between its nodes (small-world networks).  It is therefore safe to state that the field of Complex Networks (sometimes called Network Sciences) is one of the most promising interdisciplinary disciplines of today. The sample of works in this book gives as a taste of what is in the horizon such controlling the dynamics of a network and in the network, using social interactions to improve urban planning, ranking in music and other art forms, and the understanding of knowledge transfer in influence networks.
650 0 _aEngineering.
650 0 _aPhysics.
650 1 4 _aEngineering.
650 2 4 _aComputational Intelligence.
650 2 4 _aComplexity.
650 2 4 _aComplex Networks.
700 1 _aEvsukoff, Alexandre.
_eeditor.
700 1 _aGonzález, Marta C.
_eeditor.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9783642302862
830 0 _aStudies in Computational Intelligence,
_x1860-949X ;
_v424
856 4 0 _uhttp://dx.doi.org/10.1007/978-3-642-30287-9
912 _aZDB-2-ENG
999 _c96981
_d96981