KDD 2004: Conference Panels

Awards at SIGKDD-2004

The following awards were presented at KDD-2004

Best Research Paper Award

The KDD-2004 best research paper award went to Sugato Basu, Mikhail Bilenko, and Raymond Mooney for the paper titled A Probabilistic Framework for Semi-Supervised Clustering

Best Applications Paper Award

The KDD-2004 best applications award went to Jeremy Kolter and Marcus A. Maloof for the paper titled Learning to Detect Malicious Executables in the Wild.

Best Student Paper Award

This year's best student paper prize was awarded to Xiaoyun Wu (co-authored with Rohini Srihari) for the paper Incorporating Prior Knowledge with Weighted Margin Support Vector Machines

KDD-Cup Awards

Protein task winners.

Physics task winners.

SIGKDD Innovation Award

The 2004 SIGKDD Innovation Award went to Jiawei Han, Professor, Computer Science, at Univ. of Illinois at Urbana-Champaign.

Dr. Han is widely and well regarded as a pioneer researcher in data mining and knowledge discovery, who has made many fundamental research contributions, including

Novel and efficient algorithms for frequent pattern mining, e.g., FP-tree and graph pattern mining algorithms
Attribute-oriented induction methods
Spatial data mining and clustering
Stream mining
Data warehousing
Innovative schemes to integrate OLAP, data warehouse and data mining.

The impact of Dr. Han's work is well illustrated by his paper on mining frequent patterns without candidate generation. Unlike earlier approaches that first generated candidates and then counted their support, this radically different approach essentially merged candidate generation and counting. This is done using a novel database structure, the FP-tree, which condenses the set of transactions into a form that is more compact than the original representation and amenable to a new depth-first pattern search method called FP-Growth. FP-tree based approaches are among the leading state of the art techniques for frequent itemset mining, and the concepts have also proven useful for other patterns (sequences, episodes) and pattern types (maximal, closed).

He has published more than 100 research papers on data mining in leading database and data mining conferences and journals, such as SIGMOD, VLDB, KDD, ICDE, EDBT, TKDE, and TOIS. His contribution can be seen in almost every area of the field.

Because of his many seminal contributions, Dr. Han is a very highly cited author, with over 3,000 citations, according to Citeseer. This clearly indicates the quality of his work, his influence in the field, and his contributions to many topics of data mining.

Jiawei not only is dedicated to pure research, but also industrial applications, benchmarking and products. He was the founder and chief architect of DBMiner, one of the first generation data mining products. He also actively led several projects on industrial applications of data mining techniques, which showcase the value and potential of the data mining technology.

SIGKDD Service Award

The 2004 SIGKDD service award went to Xindong Wu, Professor and Chairman of the Computer Science Department at the University of Vermont.

He was the Founding Chair (April 1998 - April 2001) of the Steering Committee for the Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), which has become the leading Asian data mining conference. He served as a program chair of PAKDD 98.

In 1999, he started the Knowledge and Information System (KAIS) journal and served as the Executive Editor since then. KAIS has become one of the main journals for publishing data mining related research .

In 2001 he founded the IEEE International Conference on Data Mining (ICDM) which has quickly become one of the premier conferences in the data mining field, receiving about 500 submissions in 2003-2004. He currently serves as the Chair of the Steering Committee for the IEEE International Conference on Data Mining (ICDM) and Chair of the IEEE Computer Society Technical Committee on Computational Intelligence (TCCI). He has been working tirelessly to promote the data mining field in the IEEE community and in the world.

In addition to his significant service contributions, Dr. Xindong Wu is also very active and productive in data mining research and has an excellent track record of publications including eight books (author of two, co-author of one and co-ed of five) and numerous journal and conference papers in data mining.

Research Paper Award, Runner-up

The runner-up for this year's best research paper award is The Complexity of Mining Maximal Frequent Itemsets and Maximal Frequent Patterns by Guizhen Yang Mining Coherent Gene Clusters from Three-

Applications Paper Award, Runner-up

The runner-up for this year's best applications paper award is Mining Coherent Gene Clusters from Three-Dimensional Microarray Data, by Daxin Jiang, Jian Pei, Murali Ramanathan, Chun Tang, and Aidong Zhang.