COVER
Table of contents
List of figures
List of tables
Notations & Abbreviations
Chapter 1. Introduction to Data mining
1.1 Data mining
1.1.1 Data mining: Motivation
1.1.2 Data mining: Definition
1.1.3 Main steps in Knowledge discovery in databases (KDD)
1.1 Major approaches and techniques in Data mining
1.2.1 Major approaches and techniques in Data mining
1.2.2 Kinds of data could be mined
1.2 Applications of Data mining
1.2.1 Applications of Data mining
1.2.2 Classification of Data mining systems
1.3 Focused issues in Data mining
Chapter 2. Association rules
2.1 Association rules: Motivation
2.2 Association rules mining - Problem statement
2.3 Main research trends in Association rules mining
Chapter 3. Fuzzy association rules mining
3.1 Quantitative association rules
3.1.1 Association rules with quantitative and categorical attributes
3.1.2 Methods of data discretization
3.2 Fuzzy association rules
3.2.1 Data discretization based on fuzzy set
3.2.2 Fuzzy associat ion rules
3.2.3 Algorithm for fuzzy association rules mining
3.2.4 Relation between fuzzy association rules and quantitative ones
3.2.5 Experiments and conclusions
Chapter 4. Parallel mining of fuzzy association rules
4.1 Several previously proposed parallel algorithms
4.2 A new parallel algorithm for fuzzy association rules mining
4.2.1 Our approach
4.2.2 The new algorithm
4.2.3 Proof of correctness and computational complexity
4.3 Experiments and conclusions
Conclusion
Reference
Appendix