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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...
| Clasificación: | Libro Electrónico |
|---|---|
| Autor Corporativo: | |
| Otros Autores: | , , |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Berlin, Heidelberg :
Springer Berlin Heidelberg : Imprint: Springer,
2006.
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| Edición: | 1st ed. 2006. |
| Temas: | |
| Acceso en línea: | Texto Completo |
MARC
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| 001 | 978-3-540-28349-2 | ||
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| 024 | 7 | |a 10.1007/3-540-28349-8 |2 doi | |
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| 245 | 1 | 0 | |a Grouping Multidimensional Data |h [electronic resource] : |b Recent Advances in Clustering / |c edited by Jacob Kogan, Charles Nicholas, Marc Teboulle. |
| 250 | |a 1st ed. 2006. | ||
| 264 | 1 | |a Berlin, Heidelberg : |b Springer Berlin Heidelberg : |b Imprint: Springer, |c 2006. | |
| 300 | |a XII, 268 p. |b online resource. | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
| 338 | |a online resource |b cr |2 rdacarrier | ||
| 347 | |a text file |b PDF |2 rda | ||
| 505 | 0 | |a 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. | |
| 520 | |a 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 anomaly detection. Kogan and his co-editors have put together recent advances in clustering large and high-dimension data. Their volume addresses new topics and methods which are central to modern data analysis, with particular emphasis on linear algebra tools, opimization methods and statistical techniques. The contributions, written by leading researchers from both academia and industry, cover theoretical basics as well as application and evaluation of algorithms, and thus provide an excellent state-of-the-art overview. The level of detail, the breadth of coverage, and the comprehensive bibliography make this book a perfect fit for researchers and graduate students in data mining and in many other important related application areas. | ||
| 650 | 0 | |a Data structures (Computer science). | |
| 650 | 0 | |a Information theory. | |
| 650 | 0 | |a Information storage and retrieval systems. | |
| 650 | 0 | |a Statistics . | |
| 650 | 0 | |a Computer science-Mathematics. | |
| 650 | 0 | |a Mathematical statistics-Data processing. | |
| 650 | 0 | |a Pattern recognition systems. | |
| 650 | 1 | 4 | |a Data Structures and Information Theory. |
| 650 | 2 | 4 | |a Information Storage and Retrieval. |
| 650 | 2 | 4 | |a Statistical Theory and Methods. |
| 650 | 2 | 4 | |a Mathematical Applications in Computer Science. |
| 650 | 2 | 4 | |a Statistics and Computing. |
| 650 | 2 | 4 | |a Automated Pattern Recognition. |
| 700 | 1 | |a Kogan, Jacob. |e editor. |4 edt |4 http://id.loc.gov/vocabulary/relators/edt | |
| 700 | 1 | |a Nicholas, Charles. |e editor. |4 edt |4 http://id.loc.gov/vocabulary/relators/edt | |
| 700 | 1 | |a Teboulle, Marc. |e editor. |4 edt |4 http://id.loc.gov/vocabulary/relators/edt | |
| 710 | 2 | |a SpringerLink (Online service) | |
| 773 | 0 | |t Springer Nature eBook | |
| 776 | 0 | 8 | |i Printed edition: |z 9783642066542 |
| 776 | 0 | 8 | |i Printed edition: |z 9783540814399 |
| 776 | 0 | 8 | |i Printed edition: |z 9783540283485 |
| 856 | 4 | 0 | |u https://doi.uam.elogim.com/10.1007/3-540-28349-8 |z Texto Completo |
| 912 | |a ZDB-2-SCS | ||
| 912 | |a ZDB-2-SXCS | ||
| 950 | |a Computer Science (SpringerNature-11645) | ||
| 950 | |a Computer Science (R0) (SpringerNature-43710) | ||