Soft computing for data Mining applications
The authors have consolidated their research work in this volume titled Soft Computing for Data Mining Applications. The monograph gives an insight into the research in the fields of Data Mining in combination with Soft Computing methodologies. In these days, the data continues to grow exponentially...
Uloženo v:
| Hlavní autoři: | , , |
|---|---|
| Médium: | Livre numérique |
| Jazyk: | Anglais |
| Vydáno: |
Berlin, Heidelberg :
Springer Berlin Heidelberg
[20..].
Cham : Springer Nature |
| Vydání: | 1st ed. 2009. |
| Edice: | Studies in Computational Intelligence
190 |
| On-line přístup: | Accès sur la plateforme de l'éditeur Accès sur la plateforme Istex Accès Université d'Orléans Accès INSA CVL |
| Poznámka: |
Archives Springer e-books (Licence nationale) Archives Springer e-books (Licence nationale) |
| Autres localisations: | Voir dans le Sudoc |
| Edition sous un autre format: | • Soft Computing for Data Mining Applications, Texte imprimé, 9783642001925 |
Obsah:
- 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