Data Analysis and Pattern Recognition in Multiple Databases

1. Introduction
Animesh Adhikari, Jhimli Adhikari, Witold Pedrycz

2. Synthesizing Different Extreme Association Rules from Multiple Databases
Animesh Adhikari, Jhimli Adhikari, Witold Pedrycz

3. Clustering Items in Time-Stamped Databases Induced by Stability
Animesh Adhikari, Jhimli Adhikari, Witold Pedrycz

4. Synthesizing Global Patterns in Multiple Large Data Sources
Animesh Adhikari, Jhimli Adhikari, Witold Pedrycz

5. Clustering Local Frequency Items in Multiple Data Sources
Animesh Adhikari, Jhimli Adhikari, Witold Pedrycz

6. Mining Patterns of Select Items in Different Data Sources
Animesh Adhikari, Jhimli Adhikari, Witold Pedrycz

7. Synthesizing Global Exceptional Patterns in Different Data Sources
Animesh Adhikari, Jhimli Adhikari, Witold Pedrycz

8. Mining Icebergs in Different Time-Stamped Data Sources
Animesh Adhikari, Jhimli Adhikari, Witold Pedrycz

9. Mining Calendar-Based Periodic Patterns in Time-Stamped Data
Animesh Adhikari, Jhimli Adhikari, Witold Pedrycz

10. Measuring Influence of an Item in Time-Stamped Databases
Animesh Adhikari, Jhimli Adhikari, Witold Pedrycz

11. Summary and Conclusions
Animesh Adhikari, Jhimli Adhikari, Witold Pedrycz

Avainsanat: Engineering, Computational Intelligence, Pattern Recognition, Data Mining and Knowledge Discovery