000			03220nam a2200481 i 4500
001			EBC1591690
003			MiAaPQ
005			20240120153608.0
006			m o d |
007			cr cnu||||||||
008			140902t20152015flua ob 001 0 eng|d
020			_z9781466584518 (hardback)
020			_a9781466584525 (e-book)
035			_a(MiAaPQ)EBC1591690
035			_a(Au-PeEL)EBL1591690
035			_a(CaPaEBR)ebr10961798
035			_a(CaONFJC)MIL695111
035			_a(OCoLC)894611737
040			_aMiAaPQ _beng _erda _epn _cMiAaPQ _dMiAaPQ
050		4	_aQA166 _b.Q36 2015
082	0		_a511/.5 _223
245	0	0	_aQuantitative graph theory : _bmathematical foundations and applications / _cedited by Matthias Dehmer, Frank Emmert-Streib.
264		1	_aBoca Raton : _bCRC Press, _c[2015]
264		4	_c2015
300			_a1 online resource (516 pages) : _billustrations.
336			_atext _2rdacontent
337			_acomputer _2rdamedia
338			_aonline resource _2rdacarrier
490	1		_aDiscrete mathematics and its applications
504			_aIncludes bibliographical references and index.
520			_a"Graph-based approaches have been employed extensively in several disciplines such as biology, computer science, chemistry, and so forth. In the 1990s, exploration of the topology of complex networks became quite popular and was triggered by the breakthrough of the Internet and the examinations of random networks. As a consequence, the structure of random networks has been explored using graph-theoretic methods and stochastic growth models. However, it turned out that besides exploring random graphs, quantitative approaches to analyze networks are crucial as well. This relates to quantifying structural information of complex networks by using ameasurement approach. As demonstrated in the scientific literature, graph- and informationtheoretic measures, and statistical techniques applied to networks have been used to do this quantification. It has been found that many real-world networks are composed of network patterns representing nonrandom topologies.Graph- and information-theoretic measures have been proven efficient in quantifying the structural information of such patterns. The study of relevant literature reveals that quantitative graph theory has not yet been considered a branch of graph theory"-- _cProvided by publisher.
588			_aDescription based on print version record.
590			_aElectronic reproduction. Ann Arbor, MI : ProQuest, 2015. Available via World Wide Web. Access may be limited to ProQuest affiliated libraries.
650		0	_aGraph theory _xData processing.
650		0	_aCombinatorial analysis.
655		4	_aElectronic books.
700	1		_aDehmer, Matthias, _d1968- _eeditor.
700	1		_aEmmert-Streib, Frank, _eeditor.
776	0	8	_iPrint version: _tQuantitative graph theory : mathematical foundations and applications. _dBoca Raton : CRC Press, [2015] _kDiscrete mathematics and its applications _z9781466584518 _w(DLC)10961798
797	2		_aProQuest (Firm)
830		0	_aDiscrete mathematics and its applications.
856	4	0	_uhttps://ebookcentral.proquest.com/lib/bacm-ebooks/detail.action?docID=1591690 _zClick to View
999			_c106856 _d106856