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.

List of contents

The Mathematics of Learning.- Logical Regression Analysis: From Mathematical Formulas to Linguistic Rules.- A Feature/Attribute Theory for Association Mining and Constructing the Complete Feature Set.- A New Theoretical Framework for K-means-type Clustering.- Clustering via Decision Tree Construction.- Incremental Mining on Association Rules.- Mining Association Rules from Tabular Data Guided by Maximal Frequent Itemsets.- Sequential Pattern Mining by Pattern-Growth: Principles and Extensions.- Web Page Classification.- Web Mining - Concepts, Applications, and Research Directions.- Privacy-Preserving Data Mining.

Summary

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.

Product details

• Assisted by: W. Chu (Editor), Wesle Chu (Editor), Wesley Chu (Editor), Tsau Young Lin (Editor), Young Lin (Editor), Young Lin (Editor)
• Publisher: Springer, Berlin
• Languages: English
• Product format: Hardback
• Released: 22.09.2005
• EAN: 9783540250579
• ISBN: 978-3-540-25057-9
• No. of pages: 342
• Weight: 646 g
• Illustrations: X, 342 p.
• Series: Studies in Fuzziness and Soft Computing; Studies in Fuzziness and Soft Computing
• Subjects: Natural sciences, medicine, IT, technology > IT, data processing > IT; B, Artificial Intelligence, Netzwerk-Hardware, engineering, Theory of Computation, Applications of Mathematics, Mathematical and Computational Engineering, Information Systems and Communication Service, Computers, Information theory, Engineering mathematics, Mathematical theory of computation, Applied mathematics, Mathematical and Computational Engineering Applications, Maths for engineers, Information and Communication, Circuits, Database Management System, Computer networking & communications