04208nam 22007215 450 991029846830332120200919063014.03-662-46193-510.1007/978-3-662-46193-8(CKB)3710000000412249(EBL)2095358(SSID)ssj0001500745(PQKBManifestationID)11918249(PQKBTitleCode)TC0001500745(PQKBWorkID)11520393(PQKB)10587263(DE-He213)978-3-662-46193-8(MiAaPQ)EBC2095358(PPN)186027257(EXLCZ)99371000000041224920150508d2015 u| 0engur|n|---|||||txtccrIntelligent Knowledge[electronic resource] A Study beyond Data Mining /by Yong Shi, Lingling Zhang, Yingjie Tian, Xingsen Li1st ed. 2015.Berlin, Heidelberg :Springer Berlin Heidelberg :Imprint: Springer,2015.1 online resource (160 p.)SpringerBriefs in Business,2191-5482Description based upon print version of record.3-662-46192-7 Includes bibliographical references and index.Dedication -- 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.This 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.SpringerBriefs in Business,2191-5482Information technologyBusiness—Data processingBusiness ethicsBusiness mathematicsIT in Businesshttps://scigraph.springernature.com/ontologies/product-market-codes/522000Business Ethicshttps://scigraph.springernature.com/ontologies/product-market-codes/526000Business Mathematicshttps://scigraph.springernature.com/ontologies/product-market-codes/523000Information technology.Business—Data processing.Business ethics.Business mathematics.IT in Business.Business Ethics.Business Mathematics.006.312Shi Yongauthttp://id.loc.gov/vocabulary/relators/aut598062Zhang Linglingauthttp://id.loc.gov/vocabulary/relators/autTian Yingjieauthttp://id.loc.gov/vocabulary/relators/autLi Xingsenauthttp://id.loc.gov/vocabulary/relators/autMiAaPQMiAaPQMiAaPQBOOK9910298468303321Intelligent Knowledge2540347UNINA