Data Mining and Knowledge Discovery via Logic-Based Methods

1. Introduction
Evangelos Triantaphyllou

2. Inferring a Boolean Function from Positive and Negative Examples
Evangelos Triantaphyllou

3. A Revised Branch-and-Bound Approach for Inferring a Boolean Function from Examples
Evangelos Triantaphyllou

4. Some Fast Heuristics for Inferring a Boolean Function from Examples
Evangelos Triantaphyllou

5. An Approach to Guided Learning of Boolean Functions
Evangelos Triantaphyllou

6. An Incremental Learning Algorithm for Inferring Boolean Functions
Evangelos Triantaphyllou

7. A Duality Relationship Between Boolean Functions in CNF and DNF Derivable from the Same Training Examples
Evangelos Triantaphyllou

8. The Rejectability Graph of Two Sets of Examples
Evangelos Triantaphyllou

9. The Reliability Issue in Data Mining: The Case of Computer-Aided Breast Cancer Diagnosis
Evangelos Triantaphyllou

10. Data Mining and Knowledge Discovery by Means of Monotone Boolean Functions
Evangelos Triantaphyllou

11. Some Application Issues of Monotone Boolean Functions
Evangelos Triantaphyllou

12. Mining of Association Rules
Evangelos Triantaphyllou

13. Data Mining of Text Documents
Evangelos Triantaphyllou

14. First Case Study: Predicting Muscle Fatigue from EMG Signals
Evangelos Triantaphyllou

15. Second Case Study: Inference of Diagnostic Rules for Breast Cancer
Evangelos Triantaphyllou

16. A Fuzzy Logic Approach to Attribute Formalization: Analysis of Lobulation for Breast Cancer Diagnosis
Evangelos Triantaphyllou

17. Conclusions
Evangelos Triantaphyllou

Keywords: Mathematics, Operations Research, Mathematical Programming, Mathematical Logic and Formal Languages, Operations Research/Decision Theory