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Data Mining for Business Applications

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Cover of 'Data Mining for Business Applications'

Table of Contents

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    Book Overview
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    Chapter 1 Introduction to Domain Driven Data Mining
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    Chapter 2 Post-processing Data Mining Models for Actionability
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    Chapter 3 On Mining Maximal Pattern-Based Clusters
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    Chapter 4 Role of Human Intelligence in Domain Driven Data Mining
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    Chapter 5 Ontology Mining for Personalized Search
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    Chapter 6 Data Mining Applications in Social Security
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    Chapter 7 Security Data Mining: A Survey Introducing Tamper-Resistance
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    Chapter 8 A Domain Driven Mining Algorithm on Gene Sequence Clustering
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    Chapter 9 Data Mining for Business Applications
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    Chapter 10 Data Mining for Business Applications
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    Chapter 11 Microarray Data Mining: Selecting Trustworthy Genes with Gene Feature Ranking
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    Chapter 12 Blog Data Mining for Cyber Security Threats
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    Chapter 13 Blog Data Mining: The Predictive Power of Sentiments
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    Chapter 14 Web Mining: Extracting Knowledge from the World Wide Web
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    Chapter 15 DAG Mining for Code Compaction
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    Chapter 16 A Framework for Context-Aware Trajectory
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    Chapter 17 Census Data Mining for Land Use Classification
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    Chapter 18 Visual Data Mining for Developing Competitive Strategies in Higher Education
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    Chapter 19 Data Mining For Robust Flight Scheduling
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    Chapter 20 Data Mining for Algorithmic Asset Management
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1 Wikipedia page

Citations

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Title
Data Mining for Business Applications
Published by
Springer US, January 2009
DOI 10.1007/978-0-387-79420-4
ISBNs
978-0-387-79419-8, 978-0-387-79420-4, 978-1-4419-4635-5
Editors

Longbing Cao, Philip S. Yu, Chengqi Zhang, Huaifeng Zhang

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 134 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Portugal 1 <1%
Germany 1 <1%
France 1 <1%
Norway 1 <1%
Ireland 1 <1%
India 1 <1%
Belgium 1 <1%
United States 1 <1%
Unknown 126 94%

Demographic breakdown

Readers by professional status Count As %
Student > Master 31 23%
Student > Ph. D. Student 23 17%
Student > Bachelor 10 7%
Student > Doctoral Student 8 6%
Researcher 6 4%
Other 25 19%
Unknown 31 23%
Readers by discipline Count As %
Computer Science 55 41%
Business, Management and Accounting 12 9%
Engineering 10 7%
Economics, Econometrics and Finance 7 5%
Social Sciences 6 4%
Other 10 7%
Unknown 34 25%