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Intelligent knowledge = a study beyo...

Shi, Yong.

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Intelligent knowledge = a study beyond data mining /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Intelligent knowledge/ by Yong Shi ... [et al.].
其他題名:	a study beyond data mining /
其他作者:	Shi, Yong.
出版者:	Berlin, Heidelberg :Springer Berlin Heidelberg : : 2015.,
面頁冊數:	xvi, 150 p. :ill. (some col.), digital ;24 cm.
內容註:	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
標題:	Data mining. -
電子資源:	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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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.
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