Soft Computing for Data Mining Applications
| Autores principales: | , , |
|---|---|
| Autor Corporativo: | |
| Formato: | eBook |
| Lenguaje: | English |
| Publicado: |
Berlin, Heidelberg :
Springer Berlin Heidelberg : Imprint: Springer,
2009.
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| Edición: | 1st ed. 2009. |
| Colección: | Studies in Computational Intelligence,
190 |
| Materias: | |
| Acceso en línea: | https://doi.org/10.1007/978-3-642-00193-2 |
Tabla de Contenidos:
- Self Adaptive Genetic Algorithms
- Characteristic Amplification Based Genetic Algorithms
- Dynamic Association Rule Mining Using Genetic Algorithms
- Evolutionary Approach for XML Data Mining
- Soft Computing Based CBIR System
- Fuzzy Based Neuro - Genetic Algorithm for Stock Market Prediction
- Data Mining Based Query Processing Using Rough Sets and GAs
- Hashing the Web for Better Reorganization
- Algorithms for Web Personalization
- Classifying Clustered Webpages for Effective Personalization
- Mining Top - k Ranked Webpages Using SA and GA
- A Semantic Approach for Mining Biological Databases
- Probabilistic Approach for DNA Compression
- Non-repetitive DNA Compression Using Memoization
- Exploring Structurally Similar Protein Sequence Motifs
- Matching Techniques in Genomic Sequences for Motif Searching
- Merge Based Genetic Algorithm for Motif Discovery.