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...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autores principales: Venugopal, K. R. (Autor), Srinivasa, K.G (Autor), Patnaik, L. M. (Autor)
Autor Corporativo: SpringerLink (Online service)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2009.
Edición:1st ed. 2009.
Colección:Studies in Computational Intelligence, 190
Temas:
Computer-aided engineering.
Engineering mathematics.
Engineering-Data processing.
Artificial intelligence.
Computer-Aided Engineering (CAD, CAE) and Design.
Mathematical and Computational Engineering Applications.
Artificial Intelligence.
Acceso en línea:Texto Completo
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.

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