000			02755nam a2200409 i 4500
001			CR9781009118897
003			UkCbUP
005			20240508141513.0
006			m|||||o||d||||||||
007			cr |||||||||||
008			230628s2023 enka fob 000|0 eng|d
020			_a9781009118897 _qebook _cNo price
020			_z9781009113007 _qpaperback _cNo price
024	7		_a10.1017/9781009118897 _2doi
040			_aStDuBDS _beng _cStDuBDS _erda _epn
050		4	_aHM741 _b.P4 2023
082	0	4	_a302.011 _223
100	1		_aPeixoto, Tiago, _eauthor.
245	1	0	_aDescriptive vs. inferential community detection in networks : _bpitfalls, myths and half-truths / _cTiago P. Peixoto.
264		1	_aCambridge : _bCambridge University Press, _c2023.
300			_a1 online resource (75 pages) : _billustrations (black and white, and colour), digital, PDF file(s).
336			_atext _btxt _2rdacontent
336			_astill image _bsti _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
490	1		_aCambridge elements. Elements in the structure and dynamics of complex networks, _x2516-5763
500			_aAlso issued in print: 2023.
504			_aIncludes bibliographical references.
506	0		_aOpen Access. _fUnrestricted online access _2star
520	8		_aCommunity detection is one of the most important methodological fields of network science, and one which has attracted a significant amount of attention over the past decades. This area deals with the automated division of a network into fundamental building blocks, with the objective of providing a summary of its large-scale structure. Despite its importance and widespread adoption, there is a noticeable gap between what is arguably the state-of-the-art and the methods which are actually used in practice in a variety of fields. The Elements attempts to address this discrepancy by dividing existing methods according to whether they have a 'descriptive' or an 'inferential' goal. While descriptive methods find patterns in networks based on context-dependent notions of community structure, inferential methods articulate a precise generative model, and attempt to fit it to data. In this way, they are able to provide insights into formation mechanisms and separate structure from noise. This title is also available as open access on Cambridge Core.
521			_aSpecialized.
588			_aDescription based on online resource; title from PDF title page (viewed on July 24, 2023).
650		0	_aSocial networks _xResearch _xMethodology.
776	0	8	_iPrint version : _z9781009113007
830		0	_aCambridge elements. _pElements in the structure and dynamics of complex networks, _x2516-5763.
856	4	0	_uhttps://doi.org/10.1017/9781009118897
999			_c38448 _d38448