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Data Mining: Foundations and Intelligent Paradigms Volume 3: Medical, Health, Social, Biological and other Applications

Data mining is one of the most rapidly growing research areas in computer science and statistics. In Volume 3 of this three volume series, we have brought together contributions from some of the most prestigious researchers in applied data mining. Areas of application covered are diverse and include...

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Bibliographic Details
Other Authors: Holmes, Dawn E. (Editor), Jain, Lakhmi C. (Editor)
Format: eBook
Language:English
Published: Berlin, Heidelberg Springer Berlin Heidelberg 2012, 2012
Edition:1st ed. 2012
Series:Intelligent Systems Reference Library
Subjects:
Operations Research
Computational Intelligence
Artificial Intelligence
Operations Research And Decision Theory
Online Access:
Collection: Springer eBooks 2005- - Collection details see MPG.ReNa
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505 0 |a From the content: Advances in Data Mining Applications -- Temporal Pattern Mining for Medical Applications -- BioKeySpotter: an Unsupervised Keyphrase Extraction Technique in the Biomedical Full-text Collection -- Mining Health Claims data for assessing patient risk -- Mining biological networks for similar patterns -- Estimation of Distribution Algorithms in Gene Expression Data Analysis 
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520 |a Data mining is one of the most rapidly growing research areas in computer science and statistics. In Volume 3 of this three volume series, we have brought together contributions from some of the most prestigious researchers in applied data mining. Areas of application covered are diverse and include healthcare and finance. Each of the chapters is self contained. Statisticians, applied scientists/ engineers and researchers in bioinformatics will find this volume valuable. Additionally, it provides a sourcebook for graduate students interested in the current direction of research in applied data mining 

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