Entries tagged with Innovation Award

2006 SIGKDD Innovation Award: Dr. Ramakrishnan Srikant

2006 SIGKDD Innovation Award: Dr. Ramakrishnan Srikant: 2006 SIGKDD Innovation Award Winner

Srikant identified novel pruning techniques and data structures that made the discovery of association rules feasible. He also generalized association rules along three orthogonal dimensions: discovering associations across different levels of a hierarchy over the items; discovering temporal associations ("sequential patterns"); and discovering associations over quantitative attributes. In each case, Srikant invented pruning techniques and data structures that kept the execution times practical.

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2005 SIGKDD Innovation Award: Dr. Leo Breiman

2005 SIGKDD Innovation Award: Dr. Leo Breiman: 2005 SIGKDD Innovation Award Winner

Dr. Leo Breiman is widely considered one of the founding fathers of modern machine learning and data mining. He has been actively contributing to these fields, as well as to statistics, for more than 30 years. His best known contribution is his landmark work on decision trees.

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2004 SIGKDD Innovation Award: Dr. Jiawei Han

2004 SIGKDD Innovation Award: Dr. Jiawei Han: 2004 SIGKDD Innovation Award Winner

Dr. Han is widely and well regarded as a pioneer researcher in data mining and knowledge discovery, who has made many fundamental research contributions. He has published more than 100 research papers on data mining in leading database and data mining conferences and journals. His contribution can be seen in almost every area of the field. Dr. Han is a very highly cited author, with over 3,000 citations, indicating the quality of his work, his influence in the field, and his contributions to many topics of data mining.

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2003 SIGKDD Innovation Award: Dr. Heikki Mannila

2003 SIGKDD Innovation Award: Dr. Heikki Mannila: 2003 SIGKDD Innovation Award Winner

Professor Mannila has the rare virtue of being able to identify new problems, viewpoints, and concepts, and thereby taking the field forward. He introduced the concept of "inductive databases" that integrate data mining and databases. Equally impressive are Professor Mannila's contributions in providing a substantial and much needed theoretical foundation in a very young field. He has given strong theoretical results for many data mining problems, including association rules and frequent time sequences. The breadth of Prof Mannila's work is quite spectacular. He has over 130 articles in journals and refereed conferences covering such diverse topics as association rules, probabilistic modeling, inductive databases, similar time series, and bio-informatics.

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2002 SIGKDD Innovation Award: Dr. Jerome H. Friedman

2002 SIGKDD Innovation Award: Dr. Jerome H. Friedman: 2002 SIGKDD Innovation Award Winner

Jerry Friedman has contributed a remarkable array of topics and methodologies to data mining and machine learning during the last 25 years. Taken together, Dr. Friedman's list of contributions to new methodology, including CART, MARS, PRIM, PPR, and Gradient Boosting, constitutes one of the broadest ranges of any one person in the field.

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2000 SIGKDD Innovation Award: Dr. Rakesh Agrawal

2000 SIGKDD Innovation Award: Dr. Rakesh Agrawal: 2000 SIGKDD Innovation Award Winner

Rakesh Agrawal from IBM has received the first ACM SIGKDD Award for Innovation for his many research contributions, including his pioneering work on association rules, mining sequences and much more.

 

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