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Data Mining: Foundations and Intelligent Paradigms [electronic resource] : Volume 3: Medical, Health, Social, Biological and other Applications / edited by Dawn E. Holmes, Lakhmi C Jain.

By: Holmes, Dawn E [editor.].
Contributor(s): Jain, Lakhmi C [editor.] | SpringerLink (Online service).
Material type: materialTypeLabelBookSeries: Intelligent Systems Reference Library: 25Publisher: Berlin, Heidelberg : Springer Berlin Heidelberg, 2012Description: XVI, 364p. 103 illus., 37 illus. in color. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9783642231513.Subject(s): Engineering | Artificial intelligence | Engineering | Computational Intelligence | Artificial Intelligence (incl. Robotics) | Operations Research/Decision TheoryDDC classification: 006.3 Online resources: Click here to access online
Contents:
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.
In: Springer eBooksSummary: 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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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.

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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