LEADER 03720nam 2200577Ia 450 001 9910437910703321 005 20200520144314.0 010 $a3-642-30287-4 024 7 $a10.1007/978-3-642-30287-9 035 $a(CKB)3390000000030183 035 $a(SSID)ssj0000745869 035 $a(PQKBManifestationID)11378856 035 $a(PQKBTitleCode)TC0000745869 035 $a(PQKBWorkID)10859817 035 $a(PQKB)11631363 035 $a(DE-He213)978-3-642-30287-9 035 $a(MiAaPQ)EBC3070868 035 $a(PPN)168316293 035 $a(EXLCZ)993390000000030183 100 $a20120807d2013 uy 0 101 0 $aeng 135 $aurnn#008mamaa 181 $ctxt 182 $cc 183 $acr 200 10$aComplex networks /$fRonaldo Menezes, Alexandre Evsukoff, and Marta C. Gonzalez (eds.) 205 $a1st ed. 2013. 210 $aBerlin ;$aNew York $cSpringer$dc2013 215 $a1 online resource (X, 266 p.) 225 1 $aStudies in computational intelligence,$x1860-949X ;$v424 300 $aBibliographic Level Mode of Issuance: Monograph 311 $a3-642-30286-6 320 $aIncludes bibliographical references and author index. 327 $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. 330 $aIn the last decade we have seen the emergence of a new inter-disciplinary field focusing on the understanding of networks which are dynamic, large, open, and have a structure sometimes called random-biased. The field of Complex Networks is helping us better understand many complex phenomena such as the spread of  deseases, protein interactions, social relationships, to name but a few. Studies in Complex Networks are gaining attention due to some major scientific breakthroughs proposed by network scientists helping us understand and model interactions contained in large datasets. In fact, if we could point to one event leading to the widespread use of complex network analysis is the availability of online databases. Theories of Random Graphs from Erdös and Rényi from the late 1950s led us to believe that most networks had random characteristics. The work on large online datasets told us otherwise. Starting with the work of Barabási and Albert as well as Watts and Strogatz in the late 1990s, we now know that most real networks are characterized by degree distributions that fit a power law (scale-free networks), and that they are highly clustered with small average path lengths between its nodes (small-world networks).  It is therefore safe to state that the field of Complex Networks (sometimes called Network Sciences) is one of the most promising interdisciplinary disciplines of today. The sample of works in this book gives as a taste of what is in the horizon such controlling the dynamics of a network and in the network, using social interactions to improve urban planning, ranking in music and other art forms, and the understanding of knowledge transfer in influence networks. 410 0$aStudies in computational intelligence ;$vv. 424. 606 $aComputational intelligence$vCongresses 606 $aComputer networks$vCongresses 615 0$aComputational intelligence 615 0$aComputer networks 676 $a004.6 701 $aEvsukoff$b Alexandre$01763061 701 $aGonzalez$b Marta C$01763062 701 $aMenezes$b Ronaldo$0871383 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910437910703321 996 $aComplex networks$94203308 997 $aUNINA