Journeys to Data Mining

1. Front Matter

   Pages i-viii

   PDF

2. Introduction

   • Mohamed Medhat Gaber

   Pages 1-11

3. Data Mining: A Lifetime Passion

   • Dean Abbott

   Pages 13-25

4. From Combinatorial Optimization to Data Mining

   • Charu C. Aggarwal

   Pages 27-42

5. From Patterns to Discoveries

   • Michael R. Berthold

   Pages 43-49

6. Discovering Privacy

   • Chris Clifton

   Pages 51-59

7. Driving Full Speed, Eyes on the Rear-View Mirror

   • John F. Elder IV

   Pages 61-75

8. Voyages of Discovery

   • David J. Hand

   Pages 77-91

9. A Field by Any Other Name

   • Cheryl G. Howard

   Pages 93-100

10. An Unusual Journey to Exciting Data Mining Applications

    • J. Dustin Hux

    Pages 101-109

11. Making Data Analysis Ubiquitous: My Journey Through Academia and Industry

    • Hillol Kargupta

    Pages 111-130

12. Operational Security Analytics: My Path of Discovery

    • Colleen McLaughlin McCue

    Pages 131-146

13. An Enduring Interest in Classification: Supervised and Unsupervised

    • G. J. McLachlan

    Pages 147-171

14. The Journey of Knowledge Discovery

    • Gregory Piatetsky-Shapiro

    Pages 173-196

15. Data Mining: From Medical Decision Support to Hospital Management

    • Shusaku Tsumoto

    Pages 197-210

16. Rattle and Other Data Mining Tales

    • Graham J. Williams

    Pages 211-229

17. A Journey in Pattern Mining

    • Mohammed J. Zaki

    Pages 231-241

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.

• artificial intelligence
• careers in computer science
• data mining
• history of computing
• knowledge discovery in databases
• machine learning

• , School of Computing, University of Portsmouth, Portsmouth, United Kingdom

  Mohamed Medhat Gaber

Dr Mohamed Medhat Gaber is a Senior Lecturer at the University of Portsmouth, UK. He received his PhD from Monash University, Australia in 2006. He then held appointments with the University of Sydney, CSIRO, and Monash University, all in Australia. He has published more than 70 papers and edited/co-edited three books on data mining and knowledge discovery. Mohamed has served in the program committees of major conferences related to data mining, including ICDM, PAKDD, ECML/PKDD and ICML. He is recognized as a fellow of the UK Higher Education Academy (HEA); and he is also a member of the International Panel of Expert Advisers for the Australasian Data Mining Conferences. In 2007, Mohamed was awarded the CSIRO teamwork award.

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