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Applied Data Mining
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Applied Data Mining

Applied Data Mining

ByGuandong Xu, Yu Zong, Zhenglu Yang
Edition 1st Edition
First Published 2013
eBook Published 17 June 2013
Pub. location Boca Raton
Imprint CRC Press
DOIhttps://doi.org/10.1201/b15027
Pages 284 pages
eBook ISBN 9781466585843
SubjectsComputer Science, Engineering & Technology
Get Citation

Get Citation

Xu, G., Zong, Y., Yang, Z. (2013). Applied Data Mining. Boca Raton: CRC Press, https://doi.org/10.1201/b15027
ABOUT THIS BOOK

Data mining has witnessed substantial advances in recent decades. New research questions and practical challenges have arisen from emerging areas and applications within the various fields closely related to human daily life, e.g. social media and social networking. This book aims to bridge the gap between traditional data mining and the latest adv

TABLE OF CONTENTS
part |2 pages
Part I: Fundamentals
chapter 1|18 pages
Introduction
View abstract
chapter 2|24 pages
Mathematical Foundations
View abstract
chapter 3|12 pages
Data Preparation
View abstract
chapter 4|43 pages
Clustering Analysis
View abstract
chapter 5|17 pages
Classifi cation
View abstract
chapter 6|34 pages
Frequent Pattern Mining
View abstract
part |2 pages
Part II: Advanced Data Mining
chapter 7|28 pages
Advanced Clustering Analysis
View abstract
chapter 8|23 pages
Multi-Label Classifi cation
View abstract
chapter 9|9 pages
Privacy Preserving in Data Mining
View abstract
part |2 pages
Part III: Emerging Applications
chapter 10|21 pages
Data Stream
View abstract
chapter 11|12 pages
Recommendation Systems
View abstract
chapter 12|24 pages
Social Tagging Systems
View abstract

Data mining has witnessed substantial advances in recent decades. New research questions and practical challenges have arisen from emerging areas and applications within the various fields closely related to human daily life, e.g. social media and social networking. This book aims to bridge the gap between traditional data mining and the latest adv

TABLE OF CONTENTS
part |2 pages
Part I: Fundamentals
chapter 1|18 pages
Introduction
View abstract
chapter 2|24 pages
Mathematical Foundations
View abstract
chapter 3|12 pages
Data Preparation
View abstract
chapter 4|43 pages
Clustering Analysis
View abstract
chapter 5|17 pages
Classifi cation
View abstract
chapter 6|34 pages
Frequent Pattern Mining
View abstract
part |2 pages
Part II: Advanced Data Mining
chapter 7|28 pages
Advanced Clustering Analysis
View abstract
chapter 8|23 pages
Multi-Label Classifi cation
View abstract
chapter 9|9 pages
Privacy Preserving in Data Mining
View abstract
part |2 pages
Part III: Emerging Applications
chapter 10|21 pages
Data Stream
View abstract
chapter 11|12 pages
Recommendation Systems
View abstract
chapter 12|24 pages
Social Tagging Systems
View abstract
CONTENTS
ABOUT THIS BOOK

Data mining has witnessed substantial advances in recent decades. New research questions and practical challenges have arisen from emerging areas and applications within the various fields closely related to human daily life, e.g. social media and social networking. This book aims to bridge the gap between traditional data mining and the latest adv

TABLE OF CONTENTS
part |2 pages
Part I: Fundamentals
chapter 1|18 pages
Introduction
View abstract
chapter 2|24 pages
Mathematical Foundations
View abstract
chapter 3|12 pages
Data Preparation
View abstract
chapter 4|43 pages
Clustering Analysis
View abstract
chapter 5|17 pages
Classifi cation
View abstract
chapter 6|34 pages
Frequent Pattern Mining
View abstract
part |2 pages
Part II: Advanced Data Mining
chapter 7|28 pages
Advanced Clustering Analysis
View abstract
chapter 8|23 pages
Multi-Label Classifi cation
View abstract
chapter 9|9 pages
Privacy Preserving in Data Mining
View abstract
part |2 pages
Part III: Emerging Applications
chapter 10|21 pages
Data Stream
View abstract
chapter 11|12 pages
Recommendation Systems
View abstract
chapter 12|24 pages
Social Tagging Systems
View abstract

Data mining has witnessed substantial advances in recent decades. New research questions and practical challenges have arisen from emerging areas and applications within the various fields closely related to human daily life, e.g. social media and social networking. This book aims to bridge the gap between traditional data mining and the latest adv

TABLE OF CONTENTS
part |2 pages
Part I: Fundamentals
chapter 1|18 pages
Introduction
View abstract
chapter 2|24 pages
Mathematical Foundations
View abstract
chapter 3|12 pages
Data Preparation
View abstract
chapter 4|43 pages
Clustering Analysis
View abstract
chapter 5|17 pages
Classifi cation
View abstract
chapter 6|34 pages
Frequent Pattern Mining
View abstract
part |2 pages
Part II: Advanced Data Mining
chapter 7|28 pages
Advanced Clustering Analysis
View abstract
chapter 8|23 pages
Multi-Label Classifi cation
View abstract
chapter 9|9 pages
Privacy Preserving in Data Mining
View abstract
part |2 pages
Part III: Emerging Applications
chapter 10|21 pages
Data Stream
View abstract
chapter 11|12 pages
Recommendation Systems
View abstract
chapter 12|24 pages
Social Tagging Systems
View abstract
ABOUT THIS BOOK
ABOUT THIS BOOK

Data mining has witnessed substantial advances in recent decades. New research questions and practical challenges have arisen from emerging areas and applications within the various fields closely related to human daily life, e.g. social media and social networking. This book aims to bridge the gap between traditional data mining and the latest adv

TABLE OF CONTENTS
part |2 pages
Part I: Fundamentals
chapter 1|18 pages
Introduction
View abstract
chapter 2|24 pages
Mathematical Foundations
View abstract
chapter 3|12 pages
Data Preparation
View abstract
chapter 4|43 pages
Clustering Analysis
View abstract
chapter 5|17 pages
Classifi cation
View abstract
chapter 6|34 pages
Frequent Pattern Mining
View abstract
part |2 pages
Part II: Advanced Data Mining
chapter 7|28 pages
Advanced Clustering Analysis
View abstract
chapter 8|23 pages
Multi-Label Classifi cation
View abstract
chapter 9|9 pages
Privacy Preserving in Data Mining
View abstract
part |2 pages
Part III: Emerging Applications
chapter 10|21 pages
Data Stream
View abstract
chapter 11|12 pages
Recommendation Systems
View abstract
chapter 12|24 pages
Social Tagging Systems
View abstract

Data mining has witnessed substantial advances in recent decades. New research questions and practical challenges have arisen from emerging areas and applications within the various fields closely related to human daily life, e.g. social media and social networking. This book aims to bridge the gap between traditional data mining and the latest adv

TABLE OF CONTENTS
part |2 pages
Part I: Fundamentals
chapter 1|18 pages
Introduction
View abstract
chapter 2|24 pages
Mathematical Foundations
View abstract
chapter 3|12 pages
Data Preparation
View abstract
chapter 4|43 pages
Clustering Analysis
View abstract
chapter 5|17 pages
Classifi cation
View abstract
chapter 6|34 pages
Frequent Pattern Mining
View abstract
part |2 pages
Part II: Advanced Data Mining
chapter 7|28 pages
Advanced Clustering Analysis
View abstract
chapter 8|23 pages
Multi-Label Classifi cation
View abstract
chapter 9|9 pages
Privacy Preserving in Data Mining
View abstract
part |2 pages
Part III: Emerging Applications
chapter 10|21 pages
Data Stream
View abstract
chapter 11|12 pages
Recommendation Systems
View abstract
chapter 12|24 pages
Social Tagging Systems
View abstract
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