000			02338cam a22004218i 4500
005			20250919011649.0
008			160328s2014 flu b 001 0 eng
020			_a9781482226669 _qhardback _cRM458.09
039		9	_a201606231233 _bbaiti _c201606201459 _dlatihan _c201606201458 _dlatihan _c201606100853 _dros _y03-28-2016 _zros
040			_aDLC _beng _cDLC _erda _dUKM _erda
090			_aQ342.C64 3
090			_aQ342 _b.C64 3
245	0	0	_aComputational trust models and machine learning / _ceditors, Xin Liu, Anwitaman Datta, Ee-Peng Lim.
264		1	_aBoca Raton : _bTaylor & Francis, _c2015
264		4	_c©2015.
300			_axxiv, 208 pages : _billustrations ; _c24 cm.
336			_atext _2rdacontent
337			_aunmediated _2rdamedia
338			_avolume _2rdacarrier
490	1		_aChapman & Hall/CRC machine learning & pattern recognition series
504			_aIncludes bibliographical references and index.
520			_a'This book provides an introduction to computational trust models from a machine learning perspective. After reviewing traditional computational trust models, it discusses a new trend of applying formerly unused machine learning methodologies, such as supervised learning. The application of various learning algorithms, such as linear regression, matrix decomposition, and decision trees, illustrates how to translate the trust modeling problem into a (supervised) learning problem. The book also shows how novel machine learning techniques can improve the accuracy of trust assessment compared to traditional approaches'-- _cProvided by publisher.
650		0	_aComputational intelligence.
650		0	_aMachine learning.
650		0	_aTruthfulness and falsehood _xMathematical models.
700	1		_aLiu, Xin _c(Mathematician), _eeditor.
700	1		_aDatta, Anwitaman, _eeditor.
700	1		_aLim, Ee-Peng, _eeditor.
830		0	_aChapman & Hall/CRC machine learning & pattern recognition series
907			_a.b1629760x _b2019-11-12 _c2019-11-12
942			_c01 _n0 _kQ342.C64 3
914			_avtls003603070
990			_aasr
991			_aFakulti Teknologi dan Sains Maklumat
998			_al _b2016-02-03 _cm _da _feng _gflu _y0 _z.b1629760x
999			_c607329 _d607329