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Intelligent knowledge = a study beyo...

Shi, Yong.

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Intelligent knowledge = a study beyond data mining /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Intelligent knowledge/ by Yong Shi ... [et al.].
Reminder of title:	a study beyond data mining /
other author:	Shi, Yong.
Published:	Berlin, Heidelberg :Springer Berlin Heidelberg : : 2015.,
Description:	xvi, 150 p. :ill. (some col.), digital ;24 cm.
[NT 15003449]:	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.
Contained By:	Springer eBooks
Subject:	Data mining. -
Online resource:	http://dx.doi.org/10.1007/978-3-662-46193-8
ISBN:	9783662461938 (electronic bk.)

Intelligent knowledge = a study beyond data mining /
Intelligent knowledgea study beyond data mining /[electronic resource] :by Yong Shi ... [et al.]. - Berlin, Heidelberg :Springer Berlin Heidelberg :2015. - xvi, 150 p. :ill. (some col.), digital ;24 cm. - SpringerBriefs in business,2191-5482. - SpringerBriefs in business..

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.

ISBN: 9783662461938 (electronic bk.)

Standard No.: 10.1007/978-3-662-46193-8doiSubjects--Topical Terms:

562972
Data mining.

LC Class. No.: QA76.9.D343

Dewey Class. No.: 006.312

Intelligent knowledge = a study beyond data mining /
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245 0 0 $a Intelligent knowledge $h [electronic resource] : $b a study beyond data mining / $c by Yong Shi ... [et al.].
260 $a Berlin, Heidelberg : $b Springer Berlin Heidelberg : $b Imprint: Springer, $c 2015.
300 $a xvi, 150 p. : $b ill. (some col.), digital ; $c 24 cm.
490 1 $a SpringerBriefs in business, $x 2191-5482
505 0 $a 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.
520 $a 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.
650 0 $a Data mining. $3 562972
650 0 $a Big data. $3 2045508
650 1 4 $a Economics/Management Science. $3 890844
650 2 4 $a IT in Business. $3 2114922
650 2 4 $a Non-Profit Enterprises/Corporate Social Responsibility. $3 1565845
650 2 4 $a Business Mathematics. $3 2088824
700 1 $a Shi, Yong. $3 1281036
710 2 $a SpringerLink (Online service) $3 836513
773 0 $t Springer eBooks
830 0 $a SpringerBriefs in business. $3 1566391
856 4 0 $u http://dx.doi.org/10.1007/978-3-662-46193-8
950 $a Business and Economics (Springer-11643)