Holmes, Dawn E.
Data Mining: Foundations and Intelligent Paradigms Volume 3: Medical, Health, Social, Biological and other Applications / [electronic resource] : edited by Dawn E. Holmes, Lakhmi C Jain. - XVI, 364p. 103 illus., 37 illus. in color. online resource. - Intelligent Systems Reference Library, 25 1868-4394 ; . - Intelligent Systems Reference Library, 25 .
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.
9783642231513
10.1007/978-3-642-23151-3 doi
Engineering.
Artificial intelligence.
Engineering.
Computational Intelligence.
Artificial Intelligence (incl. Robotics).
Operations Research/Decision Theory.
Q342
006.3
Data Mining: Foundations and Intelligent Paradigms Volume 3: Medical, Health, Social, Biological and other Applications / [electronic resource] : edited by Dawn E. Holmes, Lakhmi C Jain. - XVI, 364p. 103 illus., 37 illus. in color. online resource. - Intelligent Systems Reference Library, 25 1868-4394 ; . - Intelligent Systems Reference Library, 25 .
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.
9783642231513
10.1007/978-3-642-23151-3 doi
Engineering.
Artificial intelligence.
Engineering.
Computational Intelligence.
Artificial Intelligence (incl. Robotics).
Operations Research/Decision Theory.
Q342
006.3