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Data Mining: Foundations and Intelligent Paradigms

Volume 3: Medical, Health, Social, Biological and other Applications

  • Book
  • © 2012

Overview

Editors:
  1. Dawn E. Holmes

    1. College of Letters & Science, Dept. Statistics & Applied Probability, University of California, Santa Barbara, Santa Barbara, USA

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  2. Lakhmi C Jain

    1. , School of Electrical and Information Eng, University of South Australia, Mawson Lakes Campus, Australia

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    You can also search for this editor in PubMed   Google Scholar

  • Contains the latest research on data mining research and its applications to financial modelling
  • The state of the art of data mining for financial modelling is presented in a handbook style
  • Written by leading experts in this field

Part of the book series: Intelligent Systems Reference Library (ISRL, volume 25)

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Table of contents (15 chapters)

  1. Front Matter

    Pages 1-13
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  2. Advances in Intelligent Data Mining

    • Dawn E. Holmes, Jeffrey W. Tweedale, Lakhmi C. Jain
    Pages 1-7

  3. Temporal Pattern Mining for Medical Applications

    • Giulia Bruno, Paolo Garza
    Pages 9-18

  4. BioKeySpotter: An Unsupervised Keyphrase Extraction Technique in the Biomedical Full-Text Collection

    • Min Song, Prat Tanapaisankit
    Pages 19-27

  5. Mining Health Claims Data for Assessing Patient Risk

    • Ian Duncan
    Pages 29-62

  6. Mining Biological Networks for Similar Patterns

    • Ferhat Ay, Günhan Gülsoy, Tamer Kahveci
    Pages 63-99

  7. Estimation of Distribution Algorithms in Gene Expression Data Analysis

    • Elham Salehi, Robin Gras
    Pages 101-121

  8. Gene Function Prediction and Functional Network: The Role of Gene Ontology

    • Erliang Zeng, Chris Ding, Kalai Mathee, Lisa Schneper, Giri Narasimhan
    Pages 123-162

  9. Mining Multiple Biological Data for Reconstructing Signal Transduction Networks

    • Thanh-Phuong Nguyen, Tu-Bao Ho
    Pages 163-185

  10. Mining Epistatic Interactions from High-Dimensional Data Sets

    • Xia Jiang, Shyam Visweswaran, Richard E. Neapolitan
    Pages 187-209

  11. Knowledge Discovery in Adversarial Settings

    • D. B. Skillicorn
    Pages 211-223

  12. Analysis and Mining of Online Communities of Internet Forum Users

    • Mikołaj Morzy
    Pages 225-263

  13. Data Mining for Information Literacy

    • Bettina Berendt
    Pages 265-297

  14. Rule Extraction from Neural Networks and Support Vector Machines for Credit Scoring

    • Rudy Setiono, Bart Baesens, David Martens
    Pages 299-320

  15. Using Self-Organizing Map for Data Mining: A Synthesis with Accounting Applications

    • Andriy Andreev, Argyris Argyrou
    Pages 321-342

  16. Applying Data Mining Techniques to Assess Steel Plant Operation Conditions

    • Khan Muhammad Badruddin, Isao Yagi, Takao Terano
    Pages 343-361

  17. Back Matter

    Pages 1-1
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Keywords

About this book

There are many invaluable books available on data mining theory and applications. However, in compiling a volume titled “DATA MINING: Foundations and Intelligent Paradigms: Volume 3: Medical, Health, Social, Biological and other Applications” we wish to introduce some of the latest developments to a broad audience of both specialists and non-specialists in this field.

Editors and Affiliations

  • College of Letters & Science, Dept. Statistics & Applied Probability, University of California, Santa Barbara, Santa Barbara, USA

    Dawn E. Holmes

  • , School of Electrical and Information Eng, University of South Australia, Mawson Lakes Campus, Australia

    Lakhmi C Jain

Bibliographic Information

  • Book Title: Data Mining: Foundations and Intelligent Paradigms

  • Book Subtitle: Volume 3: Medical, Health, Social, Biological and other Applications

  • Editors: Dawn E. Holmes, Lakhmi C Jain

  • Series Title: Intelligent Systems Reference Library

  • DOI: https://doi.org/10.1007/978-3-642-23151-3

  • Publisher: Springer Berlin, Heidelberg

  • eBook Packages: Engineering, Engineering (R0)

  • Copyright Information: Springer-Verlag Berlin Heidelberg 2012

  • Hardcover ISBN: 978-3-642-23150-6Published: 13 January 2012

  • Softcover ISBN: 978-3-642-43546-1Published: 22 February 2014

  • eBook ISBN: 978-3-642-23151-3Published: 12 January 2012

  • Series ISSN: 1868-4394

  • Series E-ISSN: 1868-4408

  • Edition Number: 1

  • Number of Pages: XVI, 364

  • Topics: Computational Intelligence, Artificial Intelligence, Operations Research/Decision Theory

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