Weka’s Winning WaysWaikato University’s Computer Science Machine Learning Group has won the 2005 SIGKDD Data Mining and Knowledge Discovery Service Award for their landmark product Weka.
The award is the highest service prize in the field of data mining and knowledge discovery. It is given to an individual or 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.
The group was recognised for their development of the freely-available Weka Data Mining Software, and the accompanying book Data Mining: Practical Machine Learning Tools and Techniques (now in second edition), which has become one of the most popular textbooks for data mining and machine learning. It is frequently cited in scientific publications.
This is the second year in a row that the Computer Science Department has received an international honour after its Digital Library Group won the biennial IFIP Namur award in 2004.
Spokesperson Professor Ian Witten says that to win two international awards in successive years, in very different areas, is quite a coup for the Computer Science Department.
“The team has put a tremendous amount of effort into continuously developing and maintaining the system,” he says. “The Weka Data Mining Software has been downloaded 200,000 times since it was put on SourceForge in April 2000. It is currently downloaded at a rate of 10,000/month. The Weka mailing list has over 1100 subscribers in 50 countries, including subscribers from many major companies.”
Professor Witten says that there are 15 well-documented substantial projects that incorporate, wrap or extend Weka, and no doubt many more that have not been reported on Sourceforge.
The award, a plaque and $2,500, is to be presented at the 11th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining being held in Chicago on August 21st.
The development of Weka was funded by a grant from the Foundation for Research, Science and Technology.
SIGKDD (Special Interest Group on Knowledge Discovery and Data Mining)
WEKA (Waikato Environment for Knowledge Analysis)
For more information please contact:
Dr Eibe Frank
Ph: 07 838 4396