Vai al contenuto principale della pagina

Intelligent Knowledge [[electronic resource] ] : A Study beyond Data Mining / / by Yong Shi, Lingling Zhang, Yingjie Tian, Xingsen Li



(Visualizza in formato marc)    (Visualizza in BIBFRAME)

Autore: Shi Yong Visualizza persona
Titolo: Intelligent Knowledge [[electronic resource] ] : A Study beyond Data Mining / / by Yong Shi, Lingling Zhang, Yingjie Tian, Xingsen Li Visualizza cluster
Pubblicazione: Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2015
Edizione: 1st ed. 2015.
Descrizione fisica: 1 online resource (160 p.)
Disciplina: 006.312
Soggetto topico: Information technology
Business—Data processing
Business ethics
Business mathematics
IT in Business
Business Ethics
Business Mathematics
Persona (resp. second.): ZhangLingling
TianYingjie
LiXingsen
Note generali: Description based upon print version of record.
Nota di bibliografia: Includes bibliographical references and index.
Nota di contenuto: 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.
Sommario/riassunto: 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.
Titolo autorizzato: Intelligent Knowledge  Visualizza cluster
ISBN: 3-662-46193-5
Formato: Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione: Inglese
Record Nr.: 9910298468303321
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Serie: SpringerBriefs in Business, . 2191-5482