Intelligent Knowledge : A Study beyond Data Mining

Yong Shi

ISBN 10: 3662461927 / ISBN 13: 9783662461921

Published by Springer Berlin Heidelberg, Springer Berlin Heidelberg, 2015

About this Item

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.

Seller Inventory # 9783662461921

Bibliographic Details

• Title: Intelligent Knowledge : A Study beyond Data Mining
• Publisher: Springer Berlin Heidelberg, Springer Berlin Heidelberg
• Publication Date: 2015
• Language: English
• ISBN 10: 3662461927
• ISBN 13: 9783662461921
• Binding: Taschenbuch
• Condition: Neu
• Dimensions: 235W x 155H x 9D millimeters 235 millimeters width by 155 millimeters height by 9 millimeters depth
• Weight: 296 grams

About this title

Synopsis

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.