Intelligent Knowledge: A Study beyond Data Mining (SpringerBriefs in Business)

Shi, Yong, Zhang, Lingling, Tian, Yingjie, Li, Xingsen

ISBN 10: 3662461927 / ISBN 13: 9783662461921

Editore: Springer, 2015

Series: SpringerBriefs in Business. Num Pages: 150 pages, 23 black & white illustrations, 24 colour illustrations, 18 black & white tables, biograp. BIC Classification: KJMV3; KJQ; UNF. Category: (G) General (US: Trade). Dimension: 163 x 237 x 9. Weight in Grams: 256. . 2015. 2015th Edition. Paperback. . . . . Books ship from the US and Ireland. Codice articolo V9783662461921

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.

Dalla quarta di copertina: 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.

Dati bibliografici

Titolo: Intelligent Knowledge: A Study beyond Data ...
Casa editrice: Springer
Data di pubblicazione: 2015
Legatura: Brossura
Condizione: New