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001 978-3-031-03766-5
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020 _a9783031037665
_9978-3-031-03766-5
024 7 _a10.1007/978-3-031-03766-5
_2doi
050 4 _aQ334-342
050 4 _aTA347.A78
072 7 _aUYQ
_2bicssc
072 7 _aCOM004000
_2bisacsh
072 7 _aUYQ
_2thema
082 0 4 _a006.3
_223
100 1 _aChen, Chen.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_979081
245 1 0 _aNetwork Connectivity
_h[electronic resource] :
_bConcepts, Computation, and Optimization /
_cby Chen Chen, Hanghang Tong.
250 _a1st ed. 2022.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2022.
300 _aXIII, 151 p.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aSynthesis Lectures on Learning, Networks, and Algorithms,
_x2690-4314
505 0 _aAcknowledgments -- Introduction -- Connectivity Measure Concepts -- Connectivity Inference Computation -- Network Connectivity Optimization -- Conclusion and Future Work -- Bibliography -- Authors' Biographies.
520 _aNetworks naturally appear in many high-impact domains, ranging from social network analysis to disease dissemination studies to infrastructure system design. Within network studies, network connectivity plays an important role in a myriad of applications. The diversity of application areas has spurred numerous connectivity measures, each designed for some specific tasks. Depending on the complexity of connectivity measures, the computational cost of calculating the connectivity score can vary significantly. Moreover, the complexity of the connectivity would predominantly affect the hardness of connectivity optimization, which is a fundamental problem for network connectivity studies. This book presents a thorough study in network connectivity, including its concepts, computation, and optimization. Specifically, a unified connectivity measure model will be introduced to unveil the commonality among existing connectivity measures. For the connectivity computation aspect, the authors introduce the connectivity tracking problems and present several effective connectivity inference frameworks under different network settings. Taking the connectivity optimization perspective, the book analyzes the problem theoretically and introduces an approximation framework to effectively optimize the network connectivity. Lastly, the book discusses the new research frontiers and directions to explore for network connectivity studies. This book is an accessible introduction to the study of connectivity in complex networks. It is essential reading for advanced undergraduates, Ph.D. students, as well as researchers and practitioners who are interested in graph mining, data mining, and machine learning.
650 0 _aArtificial intelligence.
_93407
650 0 _aCooperating objects (Computer systems).
_96195
650 0 _aProgramming languages (Electronic computers).
_97503
650 0 _aTelecommunication.
_910437
650 1 4 _aArtificial Intelligence.
_93407
650 2 4 _aCyber-Physical Systems.
_932475
650 2 4 _aProgramming Language.
_939403
650 2 4 _aCommunications Engineering, Networks.
_931570
700 1 _aTong, Hanghang.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_979082
710 2 _aSpringerLink (Online service)
_979083
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783031037764
776 0 8 _iPrinted edition:
_z9783031037566
776 0 8 _iPrinted edition:
_z9783031037863
830 0 _aSynthesis Lectures on Learning, Networks, and Algorithms,
_x2690-4314
_979084
856 4 0 _uhttps://doi.org/10.1007/978-3-031-03766-5
912 _aZDB-2-SXSC
942 _cEBK
999 _c84712
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