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Technical Inside the SQL Server Query Optimizer
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Technical Grouping Multidimensional Data: Recent Advances in Clustering
Posted on 2010-03-15
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More Publisher: Springer; 1 edition Language: english ISBN: 354028348X Paperback: 268 pages Data: February 10, 2006 Format: PDF Description: 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. - (3 Mb)
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