Biju Patnaik Central Library catalog › Details for: Data Mining: Foundations and Intelligent Paradigms Volume 3: Medical, Health, Social, Biological and other Applications /

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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: Text

TextLanguage: English Series: Intelligent Systems Reference Library: 25Publisher: Berlin, Heidelberg : Springer Berlin Heidelberg, 2012Description: XVI, 364 p. online resourceContent type: text Media type: computer Carrier type: online resourceISBN: 9783642231513Subject(s): Engineering | Artificial intelligence | Engineering | Computational Intelligence | Artificial Intelligence (incl. Robotics) | Operations Research/Decision TheoryAdditional physical formats: Printed edition:: No titleDDC classification: 006.3 LOC classification: Q342Online 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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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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