LEADER 04208nam 22007215 450 001 9910298468303321 005 20200919063014.0 010 $a3-662-46193-5 024 7 $a10.1007/978-3-662-46193-8 035 $a(CKB)3710000000412249 035 $a(EBL)2095358 035 $a(SSID)ssj0001500745 035 $a(PQKBManifestationID)11918249 035 $a(PQKBTitleCode)TC0001500745 035 $a(PQKBWorkID)11520393 035 $a(PQKB)10587263 035 $a(DE-He213)978-3-662-46193-8 035 $a(MiAaPQ)EBC2095358 035 $a(PPN)186027257 035 $a(EXLCZ)993710000000412249 100 $a20150508d2015 u| 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aIntelligent Knowledge$b[electronic resource] $eA Study beyond Data Mining /$fby Yong Shi, Lingling Zhang, Yingjie Tian, Xingsen Li 205 $a1st ed. 2015. 210 1$aBerlin, Heidelberg :$cSpringer Berlin Heidelberg :$cImprint: Springer,$d2015. 215 $a1 online resource (160 p.) 225 1 $aSpringerBriefs in Business,$x2191-5482 300 $aDescription based upon print version of record. 311 $a3-662-46192-7 320 $aIncludes bibliographical references and index. 327 $aDedication -- Preface -- Data Mining and Knowledge Management -- Foundations of Intelligent Knowledge Management -- Intelligent Knowledge and Habitual Domain -- Domain Driven Intelligent Knowledge Discovery -- Knowledge-Incorporated Multiple Criteria Linear Programming Classifiers -- Knowledge Extraction from Support Vector Machines -- Intelligent Knowledge Acquisition and Application in Customer Churn -- Intelligent Knowledge Management in Expert Mining in Traditional Chinese Medicines. 330 $aThis book is mainly about an innovative and fundamental method called ?intelligent knowledge? to bridge the gap between data mining and knowledge management, two important fields recognized by the information technology (IT) community and business analytics (BA) community respectively. The book includes definitions of the ?first-order? analytic process, ?second-order? analytic process and intelligent knowledge, which have not formally been addressed by either data mining or knowledge management. Based on these concepts, which are especially important in connection with the current Big Data movement, the book describes a framework of domain-driven intelligent knowledge discovery. To illustrate its technical advantages for large-scale data, the book employs established approaches, such as Multiple Criteria Programming, Support Vector Machine and Decision Tree to identify intelligent knowledge incorporated with human knowledge. The book further shows its applicability by means of real-life data analyses in the contexts of internet business and traditional Chinese medicines. 410 0$aSpringerBriefs in Business,$x2191-5482 606 $aInformation technology 606 $aBusiness?Data processing 606 $aBusiness ethics 606 $aBusiness mathematics 606 $aIT in Business$3https://scigraph.springernature.com/ontologies/product-market-codes/522000 606 $aBusiness Ethics$3https://scigraph.springernature.com/ontologies/product-market-codes/526000 606 $aBusiness Mathematics$3https://scigraph.springernature.com/ontologies/product-market-codes/523000 615 0$aInformation technology. 615 0$aBusiness?Data processing. 615 0$aBusiness ethics. 615 0$aBusiness mathematics. 615 14$aIT in Business. 615 24$aBusiness Ethics. 615 24$aBusiness Mathematics. 676 $a006.312 700 $aShi$b Yong$4aut$4http://id.loc.gov/vocabulary/relators/aut$0598062 702 $aZhang$b Lingling$4aut$4http://id.loc.gov/vocabulary/relators/aut 702 $aTian$b Yingjie$4aut$4http://id.loc.gov/vocabulary/relators/aut 702 $aLi$b Xingsen$4aut$4http://id.loc.gov/vocabulary/relators/aut 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910298468303321 996 $aIntelligent Knowledge$92540347 997 $aUNINA