國立虎尾科技大學 |

Developing churn models using data mining techniques and social network analysis /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Developing churn models using data mining techniques and social network analysis // by Goran Klepac, Robert Kopal and Leo Mrsic.
作者:	Klepac, Goran,
其他作者:	Kopal, Robert,
面頁冊數:	PDFs (308 pages).
附註:	"Research essentials collection".
標題:	Customer loyalty. -
電子資源:	http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/978-1-4666-6288-9
ISBN:	9781466662896 (ebook)

Developing churn models using data mining techniques and social network analysis /
Klepac, Goran,1972-

Developing churn models using data mining techniques and social network analysis /by Goran Klepac, Robert Kopal and Leo Mrsic. - PDFs (308 pages).

"Research essentials collection".

Includes bibliographical references.

Churn problem in everyday business -- Setting (realistic) business aims -- Data mining techniques for churn mitigation/detection: intrinsic attributes approach -- Social network analysis (SNA) for churn mitigation/detection: introduction and metrics -- Data preparation and churn detection -- Churn analysis using selected structured analytic techniques -- Attribute relevance analysis -- From churn models to churn solution -- Measuring predictive power -- Churn model development, monitoring, and adjustment -- Churn case studies.

Restricted to subscribers or individual electronic text purchasers.

"This book provides an in-depth analysis of attrition modeling relevant to business planning and management, offering insightful and detailed explanation of best practices, tools, and theory surrounding churn prediction and the integration of analytic tools"--Provided by publisher.

Mode of access: World Wide Web.

ISBN: 9781466662896 (ebook)

Standard No.: 10.4018/978-1-4666-6288-9doi

LCCN: 2014017276Subjects--Topical Terms:

793216
Customer loyalty.
Subjects--Index Terms:

Attribute relevance analysis

LC Class. No.: HF5415.525 / .K56 2014e

Dewey Class. No.: 658.8/342

Developing churn models using data mining techniques and social network analysis /
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100 1 $a Klepac, Goran, $d 1972- $e author. $3 1057215
245 1 0 $a Developing churn models using data mining techniques and social network analysis / $c by Goran Klepac, Robert Kopal and Leo Mrsic.
264 1 $a Hershey, Pennsylvania (701 E. Chocolate Avenue, Hershey, Pa., 17033, USA) : $b IGI Global, $c [2014]
300 $a PDFs (308 pages).
336 $a text $2 rdacontent
337 $a electronic $2 isbdmedia
338 $a online resource $2 rdacarrier
500 $a "Research essentials collection".
504 $a Includes bibliographical references.
505 0 $a Churn problem in everyday business -- Setting (realistic) business aims -- Data mining techniques for churn mitigation/detection: intrinsic attributes approach -- Social network analysis (SNA) for churn mitigation/detection: introduction and metrics -- Data preparation and churn detection -- Churn analysis using selected structured analytic techniques -- Attribute relevance analysis -- From churn models to churn solution -- Measuring predictive power -- Churn model development, monitoring, and adjustment -- Churn case studies.
506 $a Restricted to subscribers or individual electronic text purchasers.
520 3 $a "This book provides an in-depth analysis of attrition modeling relevant to business planning and management, offering insightful and detailed explanation of best practices, tools, and theory surrounding churn prediction and the integration of analytic tools"--Provided by publisher.
530 $a Also available in print.
538 $a Mode of access: World Wide Web.
650 0 $a Customer loyalty. $3 793216
650 0 $a Consumer satisfaction. $3 562610
650 0 $a Data mining. $3 528622
653 $a Attribute relevance analysis
653 $a Behavioral variables
653 $a Churn prediction
653 $a Data sampling
653 $a Predictive analytics
653 $a Risk management
653 $a Web analytics
700 1 $a Kopal, Robert, $d 1964- $e author. $3 1057216
700 1 $a Mrsic, Leo, $d 1973- $e author. $3 1057217
710 2 $a IGI Global, $e publisher. $3 1057167
856 4 1 $3 Chapter PDFs via platform: $u http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/978-1-4666-6288-9