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008			220601s2022 sz | o |||| 0|eng d
020			_a9783031037665
024	7		_a10.1007/978-3-031-03766-5 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC _dES-MaUEC
050		4	_aT57 _b2022 EB
100	1		_aChen, Chen _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _9100841
245	1	0	_aNetwork Connectivity : _bConcepts, Computation, and Optimization _cby Chen Chen, Hanghang Tong
250			_a1st edition 2022
264		1	_aCham _bSpringer International Publishing _c2022
300			_a1 recurso en línea (XIII, 151 páginas)
336			_atexto _btxt _2rdacontent
337			_aelectrónico _bc _2rdamedia
338			_arecurso electrónico _bcr _2rdacarrier
347			_aarchivo de texto _bPDF
490	0		_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.
988			_aSynthesis Collection of Technology_2022
650		7	_2embne _9145705 _aOptimización matemática
650		7	_2embne _9138446 _aAnálisis de sistemas
650		7	_2embne _9165250 _aComplejidad computacional
700	1		_aTong, Hanghang _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _9686609
776	0	8	_iPrinted edition: _z9783031037764
776	0	8	_iPrinted edition: _z9783031037566
776	0	8	_iPrinted edition: _z9783031037863
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-031-03766-5 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE
998			_b02/2023 _dz _eb _zSI