LEADER 03235oam 2200661I 450 001 9910787962603321 005 20170817211726.0 010 $a0-429-15948-X 010 $a1-4822-2667-7 024 7 $a10.1201/b17778 035 $a(CKB)2670000000560215 035 $a(EBL)1683480 035 $a(SSID)ssj0001367699 035 $a(PQKBManifestationID)11978545 035 $a(PQKBTitleCode)TC0001367699 035 $a(PQKBWorkID)11444673 035 $a(PQKB)11074376 035 $a(MiAaPQ)EBC1683480 035 $a(OCoLC)902837877 035 $a(CaSebORM)9781482226669 035 $a(PPN)197896626 035 $a(EXLCZ)992670000000560215 100 $a20180331h20152015 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 00$aComputational trust models and machine learning /$fedited by Xin Liu, EPFL, Lausanne, Switzerland, Anwitaman Datta, Nanyang Technological University, Singapore, Ee-Peng Lim, Singapore Management University 205 $a1st edition 210 1$aBoca Raton :$cTaylor & Francis,$d[2015] 210 4$dİ2015 215 $a1 online resource (227 p.) 225 1 $aChapman & Hall/CRC machine learning & pattern recognition series 300 $aA Chapman and Hall book. 311 $a1-322-63746-6 311 $a1-4822-2666-9 320 $aIncludes bibliographical references and index. 327 $aFront Cover; Series Page; Dedication; Contents; List of Figures; Preface; About the Editors; Contributors; Chapter 1: Introduction; Chapter 2: Trust in Online Communities; Chapter 3: Judging the Veracity of Claims and Reliability of Sources with Fact-Finders; Chapter 4: Web Credibility Assessment; Chapter 5: Trust-Aware Recommender Systems; Chapter 6: Biases in Trust-Based Systems; Bibliography; Back Cover 330 $aThis book provides an introduction to computational trust models from a machine learning perspective. After reviewing traditional computational trust models, it discusses a new trend of applying formerly unused machine learning methodologies, such as supervised learning. The application of various learning algorithms, such as linear regression, matrix decomposition, and decision trees, illustrates how to translate the trust modeling problem into a (supervised) learning problem. The book also shows how novel machine learning techniques can improve the accuracy of trust assessment compared to traditional approaches--$cProvided by publisher. 410 0$aChapman & Hall/CRC machine learning & pattern recognition series. 606 $aComputational intelligence 606 $aMachine learning 606 $aTruthfulness and falsehood$xMathematical models 615 0$aComputational intelligence. 615 0$aMachine learning. 615 0$aTruthfulness and falsehood$xMathematical models. 676 $a006.31 686 $aCOM037000$aCOM051240$aTEC008000$2bisacsh 702 $aLiu$b Xin$c(Mathematician), 702 $aDatta$b Anwitaman 702 $aLim$b Ee-Peng 801 0$bFlBoTFG 801 1$bFlBoTFG 906 $aBOOK 912 $a9910787962603321 996 $aComputational trust models and machine learning$93849442 997 $aUNINA