Foundations and Advances in Data Mining

• Corporate Author: SpringerLink (Online service)
• Other Authors: Chu, Wesley (Editor), Lin, Tsau Young (Editor)
• Format: Electronic eBook
• Language: English
• Published: Berlin, Heidelberg : Springer Berlin Heidelberg, 2005.
• Series: Studies in Fuzziness and Soft Computing, 180
• Subjects: Computer science.; Computers.; Artificial intelligence.; Information theory.; Applied mathematics.; Engineering mathematics.; Computer Science.; Theory of Computation.; Appl.Mathematics/Computational Methods of Engineering.; Artificial Intelligence (incl. Robotics).; Information Systems and Communication Service.; Information and Communication, Circuits.

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...

Table 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.