000 02385cam a2200421 i 4500
999 _c30779
_d30779
003 CUTN
005 20190906112300.0
008 140718s2014 fluad b 001 0 eng
020 _a9781482226669 (hardback)
041 _aEnglish
042 _apcc
082 0 0 _a006.31
_223
084 _aCOM037000
_aCOM051240
_aTEC008000
_2bisacsh
245 0 0 _aComputational trust models and machine learning /
_ceditors Xin Liu; Anwitaman Datta and Ee-Peng Lim,
260 _aBoca Raton, FL :
_bCRC Press,
_c [2015] ©2015
300 _axxiv, 208 pages :
_billustrations, charts ;
_c24 cm.
505 _t1. Introduction --
_t2. Trust in online communities --
_t3. Judging the veracity of claims and reliability of sources --
_t4. Web credibility assessment --
_t5. Trust-aware recommender systems --
_t6. Biases in trust-based systems.
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"--
650 0 _aComputational intelligence.
650 0 _aMachine learning.
650 0 _aTruthfulness and falsehood
650 7 _aCOMPUTERS / Machine Theory.
650 7 _aCOMPUTERS / Software Development & Engineering / Systems Analysis & Design.
650 7 _aTECHNOLOGY & ENGINEERING / Electronics / General.
700 1 _aLiu, Xin
700 1 _aDatta, Anwitaman.
700 1 _aLim, Ee-Peng.
942 _2ddc
_cBOOKS
490 0 _aChapman & Hall/CRC machine learning & pattern recognition series
504 _aIncludes bibliographical references (pages 175-201) and index.
650 0 _xMathematical models.
650 7 _2bisacsh
650 7 _2bisacsh
650 7 _2bisacsh
700 1 _c(Mathematician)
906 _a7
_bcbc
_corignew
_d1
_eecip
_f20
_gy-gencatlg