Grouping Multidimensional Data Recent Advances in Clustering /

Clustering is one of the most fundamental and essential data analysis techniques. Clustering can be used as an independent data mining task to discern intrinsic characteristics of data, or as a preprocessing step with the clustering results then used for classification, correlation analysis, or anom...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor Corporativo: SpringerLink (Online service)
Otros Autores: Kogan, Jacob (Editor ), Nicholas, Charles (Editor ), Teboulle, Marc (Editor )
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2006.
Edición:1st ed. 2006.
Temas:
Data structures (Computer science).
Information theory.
Information storage and retrieval systems.
Statistics .
Computer science-Mathematics.
Mathematical statistics-Data processing.
Pattern recognition systems.
Data Structures and Information Theory.
Information Storage and Retrieval.
Statistical Theory and Methods.
Mathematical Applications in Computer Science.
Statistics and Computing.
Automated Pattern Recognition.
Acceso en línea:Texto Completo
Tabla de Contenidos:
  • The Star Clustering Algorithm for Information Organization
  • A Survey of Clustering Data Mining Techniques
  • Similarity-Based Text Clustering: A Comparative Study
  • Clustering Very Large Data Sets with Principal Direction Divisive Partitioning
  • Clustering with Entropy-Like k-Means Algorithms
  • Sampling Methods for Building Initial Partitions
  • TMG: A MATLAB Toolbox for Generating Term-Document Matrices from Text Collections
  • Criterion Functions for Clustering on High-Dimensional Data.

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