Ebook: Foundations and Advances in Data Mining

With the growing use of information technology and the recent advances in web systems, the amount of data available to users has increased exponentially. Thus, there is a critical need to understand the content of the data. As a result, data-mining has become a popular research topic in recent years for the treatment of the "data rich and information poor" syndrome. In this carefully edited volume a theoretical foundation as well as important new directions for data-mining research are presented. It brings together a set of well respected data mining theoreticians and researchers with practical data mining experiences. The presented theories will give data mining practitioners a scientific perspective in data mining and thus provide more insight into their problems, and the provided new data mining topics can be expected to stimulate further research in these important directions.

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With the growing use of information technology and the recent advances in web systems, the amount of data available to users has increased exponentially. Thus, there is a critical need to understand the content of the data. As a result, data-mining has become a popular research topic in recent years for the treatment of the "data rich and information poor" syndrome. In this carefully edited volume a theoretical foundation as well as important new directions for data-mining research are presented. It brings together a set of well respected data mining theoreticians and researchers with practical data mining experiences. The presented theories will give data mining practitioners a scientific perspective in data mining and thus provide more insight into their problems, and the provided new data mining topics can be expected to stimulate further research in these important directions.

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With the growing use of information technology and the recent advances in web systems, the amount of data available to users has increased exponentially. Thus, there is a critical need to understand the content of the data. As a result, data-mining has become a popular research topic in recent years for the treatment of the "data rich and information poor" syndrome. In this carefully edited volume a theoretical foundation as well as important new directions for data-mining research are presented. It brings together a set of well respected data mining theoreticians and researchers with practical data mining experiences. The presented theories will give data mining practitioners a scientific perspective in data mining and thus provide more insight into their problems, and the provided new data mining topics can be expected to stimulate further research in these important directions.

Content:
Front Matter....Pages -
The Mathematics of Learning: Dealing with Data * ....Pages 1-19
Logical Regression Analysis: From Mathematical Formulas to Linguistic Rules....Pages 21-61
A Feature/Attribute Theory for Association Mining and Constructing the Complete Feature Set....Pages 63-78
A New Theoretical Framework for K-Means-Type Clustering....Pages 79-96
Clustering Via Decision Tree Construction....Pages 97-124
Incremental Mining on Association Rules....Pages 125-162
Mining Association Rules from Tabular Data Guided by Maximal Frequent Itemsets....Pages 163-181
Sequential Pattern Mining by Pattern-Growth: Principles and Extensions* ....Pages 183-220
Web Page Classification* ....Pages 221-274
Web Mining – Concepts, Applications and Research Directions....Pages 275-307
Privacy-Preserving Data Mining....Pages 309-340

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With the growing use of information technology and the recent advances in web systems, the amount of data available to users has increased exponentially. Thus, there is a critical need to understand the content of the data. As a result, data-mining has become a popular research topic in recent years for the treatment of the "data rich and information poor" syndrome. In this carefully edited volume a theoretical foundation as well as important new directions for data-mining research are presented. It brings together a set of well respected data mining theoreticians and researchers with practical data mining experiences. The presented theories will give data mining practitioners a scientific perspective in data mining and thus provide more insight into their problems, and the provided new data mining topics can be expected to stimulate further research in these important directions.

Content:
Front Matter....Pages -
The Mathematics of Learning: Dealing with Data * ....Pages 1-19
Logical Regression Analysis: From Mathematical Formulas to Linguistic Rules....Pages 21-61
A Feature/Attribute Theory for Association Mining and Constructing the Complete Feature Set....Pages 63-78
A New Theoretical Framework for K-Means-Type Clustering....Pages 79-96
Clustering Via Decision Tree Construction....Pages 97-124
Incremental Mining on Association Rules....Pages 125-162
Mining Association Rules from Tabular Data Guided by Maximal Frequent Itemsets....Pages 163-181
Sequential Pattern Mining by Pattern-Growth: Principles and Extensions* ....Pages 183-220
Web Page Classification* ....Pages 221-274
Web Mining – Concepts, Applications and Research Directions....Pages 275-307
Privacy-Preserving Data Mining....Pages 309-340
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