A long time ago (circa 1994-96) in a galaxy far, far away (Waikato University, Hamilton, NZ) I was involved in the team that created the original WEKA data mining software. Since then the software has evolved into a significant open-source data mining package. Ian Witten and Eibe Frank published the book Data Mining: Practical Machine Learning Tools and Techniques with Java Implementations which described how to use Eibe’s Java version (WEKA 3) (Second edition info here), and now the WEKA software has been awarded the ACM SIGKDD Service Award. From the award notice,
SIGKDD Service Award is the highest service award in the field of data mining and knowledge discovery. It is is given to one individual or one group who has performed significant service to the data mining and knowledge discovery field, including professional volunteer services in disseminating technical information to the field, education, and research funding.
Weka is a landmark system in the history of the data mining and machine learning research communities, because it is the only toolkit that has gained such widespread adoption and survived for an extended period of time (the first version of Weka was released 11 years ago). Other data mining and machine learning systems that have achieved this are individual systems, such as C4.5, not toolkits.
Since Weka is freely available for download and offers many powerful features (sometimes not found in commercial data mining software), it has become one of the most widely used data mining systems. Weka also became one of the favorite vehicles for data mining research and helped to advance it by making many powerful features available to all.
In sum, the Weka team has made an outstanding contribution to the data mining field.
The full description of WEKA, the award and the many people involved can be found here: KDnuggets News 05:13, item 2, Features.
Other related links are:
- Waikato University : Weka’s winning ways
- Waikato University Machine Learning Research Group (including WEKA download and publication pages)
- KDD05 – The Eleventh ACM SIGKDD International Conference on Knowledge Discovery and Data Mining
- Data Mining : Practical Machine Learning Tools and Techniques (Second Edition, July 2005) by Ian Witten and Eibe Frank.
When I heard about the award I went looking in my old photos and found this picture of four of us from the Waikato ML group at the International Machine Learning Conference at Lake Tahoe in 1995 (where I did a workshop presentation on the infant WEKA). From left to right – Ian Witten, Len Trigg, Stephen Garner and Craig Nevill-Manning.
Congratulations to the WEKA team. Nice to see the hard work that lots of people put in being recognised.