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Studies in Computational Intelligence #9: Foundations and Novel Approaches in Data Mining

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Studies in Computational Intelligence #9: Foundations and Novel Approaches in Data Mining Cover

 

Synopses & Reviews

Publisher Comments:

Data-mining has become a popular research topic in recent years for the treatment of the "data rich and information poor" syndrome. Currently, application oriented engineers are only concerned with their immediate problems, which results in an ad hoc method of problem solving. Researchers, on the other hand, lack an understanding of the practical issues of data-mining for realworld problems and often concentrate on issues that are of no significance to the practitioners. In this volume, we hope to remedy problems by (1) presenting a theoretical foundation of data-mining, and (2) providing important new directions for data-mining research. A set of well respected data mining theoreticians were invited to present their views on the fundamental science of data mining. We have also called on researchers with practical data mining experiences to present new important data-mining topics.

Table of Contents

From the contents Part I: Theoretical Foundations. Commonsense Causal Modeling in the Data Mining Context. Definability of Association Rules in Predicate Calculus. A Measurement-Theoretic Foundation of Rule Interestingness Evaluation. Statistical Independence as Linear Dependence in a Contingency Table. Foundations of Classification.- Part II: Novel Approaches. SVM-OD: SVM Method to Detect Outliers. Extracting Rules from Incomplete Decision Systems: System ERID. Mining for Patterns Based on Contingency Tables by KL-Miner - First Experience. Knowledge Discovery in Fuzzy Databases Using Attribute-Oriented Induction. Rough Set Strategies to Data with Missing Attribute Values. Privacy-Preserving Collaborative Data Mining.- Part III: Novel Applications. Research Issues in Web Structural Delta Mining. Workflow Reduction for Reachable-path Rediscovery in Workflow Mining. Principal Component-based Anomaly Detection Scheme. Making Better Sense of the Demographic Data Value in the Data Mining Procedure.

Product Details

ISBN:
9783642066504
Author:
Lin, Tsau Young
Publisher:
Springer
Author:
Hu, Xiaohua
Author:
Liau, Churn-Jung
Author:
Ohsuga, Setsuo
Subject:
Applied
Subject:
Data mining
Subject:
Appl.Mathematics/Computational Methods of Engineering
Subject:
Artificial Intelligence (incl. Robotics)
Subject:
Artificial Intelligence (incl. Robotics) <P>Latest results in data mining</P>
Subject:
Mathematics-Applied
Copyright:
Edition Description:
Softcover reprint of hardcover 1st ed. 2006
Series:
Studies in Computational Intelligence
Series Volume:
9
Publication Date:
20101119
Binding:
TRADE PAPER
Language:
English
Pages:
386
Dimensions:
235 x 155 mm 586 gr

Related Subjects

» Computers and Internet » Artificial Intelligence » General
» Computers and Internet » Computers Reference » General
» Science and Mathematics » Mathematics » Applied
» Science and Mathematics » Physics » Classical Mechanics

Studies in Computational Intelligence #9: Foundations and Novel Approaches in Data Mining New Trade Paper
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