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020 _a9783030972400
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024 7 _a10.1007/978-3-030-97240-0
_2doi
050 4 _aTK7885-7895
050 4 _aTK5105.5-5105.9
072 7 _aUK
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072 7 _aCOM067000
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072 7 _aUK
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082 0 4 _a621.39
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082 0 4 _a004.6
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245 1 0 _aNetwork Science
_h[electronic resource] :
_b7th International Winter Conference, NetSci-X 2022, Porto, Portugal, February 8-11, 2022, Proceedings /
_cedited by Pedro Ribeiro, Fernando Silva, José Fernando Mendes, Rosário Laureano.
250 _a1st ed. 2022.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2022.
300 _aXII, 185 p. 45 illus., 38 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
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490 1 _aInformation Systems and Applications, incl. Internet/Web, and HCI,
_x2946-1642 ;
_v13197
505 0 _aUsing localized attacks with probabilistic failures to model seismic events over physical-logical interdependent network -- A Historical Perspective On International Treaties Via Hypernetwork Science -- On the Number of Edges of the Frechet Mean and Median Graphs -- Core but not Peripheral Online Social Ties is a Protective Factor against Depression: Evidence from a Nationally Representative Sample of Young Adults -- Deep Topological Embedding with Convolutional Neural Networks for Complex Network Classification -- Modularity-based Backbone Extraction in Weighted Complex Networks -- Vessel destination prediction using a graph-based machine learning model -- Hunting for Dual-target Set on a Class of Hierarchical Networks -- Generalized Linear Models Network Autoregression -- Constructing Provably Robust Scale-free Networks -- Functional characterization of transcriptional regulatory networks of yeast species -- Competitive Information Spreading on Modular Networks -- HyperNetVec: Fast and Scalable Hierarchical Embedding for Hypergraphs.
520 _aThis book constitutes the refereed proceedings of the 7th International Conference and School of Network Science, NetSci-X 2022, held in Porto, Portugal, in February 2021. The 13 full papers were carefully reviewed and selected from 19 submissions. The papers deal with the study of network models in domains ranging from biology and physics to computer science, from financial markets to cultural integration, and from social media to infectious diseases.
650 0 _aComputer engineering.
_910164
650 0 _aComputer networks .
_931572
650 0 _aApplication software.
_9125258
650 0 _aSocial sciences
_xData processing.
_983360
650 1 4 _aComputer Engineering and Networks.
_9125259
650 2 4 _aComputer and Information Systems Applications.
_9125260
650 2 4 _aComputer Application in Social and Behavioral Sciences.
_931815
700 1 _aRibeiro, Pedro.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_9125261
700 1 _aSilva, Fernando.
_eeditor.
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_4http://id.loc.gov/vocabulary/relators/edt
_9125262
700 1 _aMendes, José Fernando.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_9125263
700 1 _aLaureano, Rosário.
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_9125264
710 2 _aSpringerLink (Online service)
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773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783030972394
776 0 8 _iPrinted edition:
_z9783030972417
830 0 _aInformation Systems and Applications, incl. Internet/Web, and HCI,
_x2946-1642 ;
_v13197
_9125266
856 4 0 _uhttps://doi.org/10.1007/978-3-030-97240-0
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