Intelligent Knowledge : A Study beyond Data Mining

Yong Shi

ISBN 10: 3662461927 / ISBN 13: 9783662461921

Editore: Springer Berlin Heidelberg, 2015

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Druck auf Anfrage Neuware - Printed after ordering - 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.

Codice articolo 9783662461921

Dati bibliografici

• Titolo: Intelligent Knowledge : A Study beyond Data Mining
• Editore: Springer Berlin Heidelberg
• Data di pubblicazione: 2015
• Lingua: Inglese
• ISBN 10: 3662461927
• ISBN 13: 9783662461921
• Rilegatura: Taschenbuch
• Condizione: Neu
• Dimensioni: 235 L x 155 A x 9 P (millimetri) 235 millimetri di larghezza per 155 millimetri di altezza per 9 millimetri di profondità
• Peso: 296 grammi

Descrizione articolo

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.