Soft Computing for Knowledge Discovery and Data Mining

Part I.Neural Network Methods

1. Introduction to Soft Computing for Knowledge Discovery and Data Mining
Oded Maimon, Lior Rokach

2. Neural Networks For Data Mining
G. Peter Zhang

3. Improved SOM Labeling Methodology for Data Mining Applications
Arnulfo Azcarraga, Ming-Huei Hsieh, Shan-Ling Pan, Rudy Setiono

Part II.Evolutionary Methods

4. A Review of evolutionary Algorithms for Data Mining
Alex A. Freitas

5. Genetic Clustering for Data Mining
Murilo Coelho Naldi, André C. P. L. F. Carvalho, Ricardo José Gabrielli Barreto Campell, eduardo Raul Hruschka

6. Discovering New Rule Induction Algorithms with Grammar-based Genetic Programming
Gisele L. Pappa, Alex A. Freitas

7. evolutionary Design of Code-matrices for Multiclass Problems
Ana Carolina Lorena, André C. P. L. F. Carvalho

Part III.Fuzzy Logic Methods

8. The Role of Fuzzy Sets in Data Mining
Lior Rokach

9. Support Vector Machines and Fuzzy Systems
Yixin Chen

10. KDD in Marketing with Genetic Fuzzy Systems
Jorge Casillas, Francisco J. Martínez-López

11. Knowledge Discovery in a Framework for Modelling with Words
Zengchang Qin, Jonathan Lawry

Part IV.Advanced Soft Computing Methods and Areas

12. Swarm Intelligence Algorithms for Data Clustering
Ajith Abraham, Swagatam Das, Sandip Roy

13. A Diffusion Framework for Dimensionality Reduction
Alon Schclar

14. Data Mining and Agent Technology: a fruitful symbiosis
Christos Dimou, Andreas L. Symeonidis, Pericles A. Mitkas

15. Approximate Frequent Itemset Mining In the Presence of Random Noise
Hong Cheng, Philip S. Yu, Jiawei Han

16. The Impact of Overfitting and Overgeneralization on the Classification Accuracy in Data Mining
Huy Nguyen Anh Pham, Evangelos Triantaphyllou

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Keywords: COMPUTERS / Computer Science COM014000