大葉大學圖書館 |

Intelligent knowledge[electronic resource] :a study beyond data mining /

紀錄類型:	書目-電子資源 : Monograph/item
杜威分類號:	006.312
書名/作者:	Intelligent knowledge : a study beyond data mining // by Yong Shi ... [et al.].
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.
Contained By:	Springer eBooks
標題:	Data mining.
標題:	Big data.
標題:	Economics/Management Science.
標題:	IT in Business.
標題:	Non-Profit Enterprises/Corporate Social Responsibility.
標題:	Business Mathematics.
ISBN:	9783662461938 (electronic bk.)
ISBN:	9783662461921 (paper)
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.
摘要、提要註:	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.
電子資源:	http://dx.doi.org/10.1007/978-3-662-46193-8

Intelligent knowledge[electronic resource] :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:

337740
Data mining.

LC Class. No.: QA76.9.D343

Dewey Class. No.: 006.312

Intelligent knowledge[electronic resource] :a study beyond data mining /
LDR:02662nmm a2200349 a 4500 001 438723
003 DE-He213
005 20151209155103.0
006 m d
007 cr nn 008maaau
008 160315s2015 gw s 0 eng d
020 $a 9783662461938 (electronic bk.)
020 $a 9783662461921 (paper)
024 7 $a 10.1007/978-3-662-46193-8 $2 doi
035 $a 978-3-662-46193-8
040 $a GP $c GP
041 0 $a eng
050 4 $a QA76.9.D343
072 7 $a KJQ $2 bicssc
072 7 $a UF $2 bicssc
072 7 $a BUS083000 $2 bisacsh
072 7 $a COM039000 $2 bisacsh
082 0 4 $a 006.312 $2 23
090 $a QA76.9.D343 $b I61 2015
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 337740
650 0 $a Big data. $3 571002
650 1 4 $a Economics/Management Science. $3 463465
650 2 4 $a IT in Business. $3 605267
650 2 4 $a Non-Profit Enterprises/Corporate Social Responsibility. $3 464458
650 2 4 $a Business Mathematics. $3 589767
700 1 $a Shi, Yong. $3 626198
710 2 $a SpringerLink (Online service) $3 463450
773 0 $t Springer eBooks
830 0 $a SpringerBriefs in business. $3 465294
856 4 0 $u http://dx.doi.org/10.1007/978-3-662-46193-8
950 $a Business and Economics (Springer-11643)

	個人資料
	儲存檢索策略
	薦購
	預約/借閱記錄查詢
	訊息
	評論
	個人書籤

	簡單查詢
	進階查詢

	指定參考書
	新書通報
	新書書單RSS