Foundations and Novel Approaches in Data Mining

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Tsau Young Lin, Setsuo Ohsuga, Churn-Jung Liau, Xiaohua Hu
Springer Science & Business Media, 2005 M11 3 - 378 pages

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 real-world 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.

 

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Contents

Commonsense Causal Modeling in the Data Mining Context
3
Definability of Association Rules in Predicate Calculus
23
A MeasurementTheoretic Foundation of Rule Interestingness Evaluation
41
Statistical Independence as Linear Dependence in a Contingency Table
61
Foundations of Classification
75
A Formal Model
99
SVM Method to Detect Outliers
129
System ERID
143
PrivacyPreserving Collaborative Data Mining
213
Impact of Purity Measures on Knowledge Extraction in Decision Trees
229
Multidimensional Online Mining
243
Quotient Space Based Cluster Analysis
259
Research Issues in Web Structural Delta Mining
273
Workflow Reduction for Reachablepath Rediscovery in Workflow Mining
289
Principal Componentbased Anomaly Detection Scheme
311
Making Better Sense of the Demographic Data Value in the Data Mining Procedure
331

Mining for Patterns Based on Contingency Tables by KLMiner First Experience
155
Knowledge Discovery in Fuzzy Databases Using AttributeOriented Induction
169
Rough Set Strategies to Data with Missing Attribute Values
197
An Effective Approach for Mining TimeSeries Gene Expression Profile
363
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