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Grouping multidimensional data : recent advances in clustering

Author: Jacob Kogan; Charles K Nicholas; M Teboulle
Publisher: Berlin ; New York : Springer, ©2006.
Edition/Format:   Print book : EnglishView all editions and formats
Summary:
"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, optimization methods and statistical techniques. The contributions, written by leading researchers from both academia and industry, cover theoretical basics as well as  Read more...
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Material Type: Internet resource
Document Type: Book, Internet Resource
All Authors / Contributors: Jacob Kogan; Charles K Nicholas; M Teboulle
ISBN: 354028348X 9783540283485
OCLC Number: 63196977
Description: xii, 268 pages : illustrations ; 25 cm
Contents: The star clustering algorithm for information organization / J.A. Aslam, E. Pelekhov and D. Rus --
A survey of clustering data mining techniques / P. Berkhin --
Similarity-based text clustering : a comparative study / J. Ghosh and A. Strehi --
Clustering very large data sets with principal direction divisive partitioning / D. Littau and D. Boley --
Clustering with entropy-like k-means algorithms / M. Teboulle, P. Berkhin, I. Dhillon, Y. Guan and J. Kogan --
Sampling methods for building initial partitions / Z. Volkovich, J. Kogan and C. Nicholas --
TMG : a MATLAB toolbox for generating term-document matrices from text collections / D. Zeimpekis and E. Gallopoulos --
Criterion functions for clustering on high-dimensional data / Y. Zhao and G. Karypis.
Responsibility: Jacob Kogan, Charles Nicholas, Marc Teboulle (eds.).
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Abstract:

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,  Read more...

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