Journeys to data mining : experiences from 15 renowned researchers
Author(s)
Bibliographic Information
Journeys to data mining : experiences from 15 renowned researchers
Springer, c2012
- : hbk.
Available at 2 libraries
  Aomori
  Iwate
  Miyagi
  Akita
  Yamagata
  Fukushima
  Ibaraki
  Tochigi
  Gunma
  Saitama
  Chiba
  Tokyo
  Kanagawa
  Niigata
  Toyama
  Ishikawa
  Fukui
  Yamanashi
  Nagano
  Gifu
  Shizuoka
  Aichi
  Mie
  Shiga
  Kyoto
  Osaka
  Hyogo
  Nara
  Wakayama
  Tottori
  Shimane
  Okayama
  Hiroshima
  Yamaguchi
  Tokushima
  Kagawa
  Ehime
  Kochi
  Fukuoka
  Saga
  Nagasaki
  Kumamoto
  Oita
  Miyazaki
  Kagoshima
  Okinawa
  Korea
  China
  Thailand
  United Kingdom
  Germany
  Switzerland
  France
  Belgium
  Netherlands
  Sweden
  Norway
  United States of America
Description and Table of Contents
Description
Data mining, an interdisciplinary field combining methods from artificial intelligence, machine learning, statistics and database systems, has grown tremendously over the last 20 years and produced core results for applications like business intelligence, spatio-temporal data analysis, bioinformatics, and stream data processing.
The fifteen contributors to this volume are successful and well-known data mining scientists and professionals. Although by no means an exhaustive list, all of them have helped the field to gain the reputation and importance it enjoys today, through the many valuable contributions they have made. Mohamed Medhat Gaber has asked them (and many others) to write down their journeys through the data mining field, trying to answer the following questions:
1. What are your motives for conducting research in the data mining field?
2. Describe the milestones of your research in this field.
3. What are your notable success stories?
4. How did you learn from your failures?
5. Have you encountered unexpected results?
6. What are the current research issues and challenges in your area?
7. Describe your research tools and techniques.
8. How would you advise a young researcher to make an impact?
9. What do you predict for the next two years in your area?
10. What are your expectations in the long term?
In order to maintain the informal character of their contributions, they were given complete freedom as to how to organize their answers. This narrative presentation style provides PhD students and novices who are eager to find their way to successful research in data mining with valuable insights into career planning. In addition, everyone else interested in the history of computer science may be surprised about the stunning successes and possible failures computer science careers (still) have to offer.
Table of Contents
Introduction.- Dean Abbott.- Charu Aggarwal.- Michael Berthold.- John Elder.- Chris Clifton.- David Hand.- Cheryl Howard.- Hillol Kargupta.- Dustin Hux.- Colleen McCue.- Geoff McLachlan.- Gregory Piatetsky-Shapiro.- Shusaku Tsumoto.- Graham Williams.- Mohammed J. Zaki.
by "Nielsen BookData"