Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining

• Authors: Won Kim;Ronny Kohavi;Johannes Gehrke;William DuMouchel
• Venue: ACM SIGKDD International Conference on Knowledge Discovery and Data Mining
• Year: 2004

KDD-2004, the Tenth ACM SIGMOD International Conference on Knowledge Discovery and Data Mining, is being held in Seattle, Washington, U.S.A., on August 22-25, 2004, with an optional day trip to Rainier National Park on August 26. KDD provides a forum for academic researchers and industry and government innovators to share in their results and experience. Data mining combines techniques and processes from allied data analytic disciplines such as statistics, machine learning, pattern recognition and visualization, while focusing on automated discovery of knowledge from databases that are often much more massive than those commonly tackled. With this conference, we mark a decade in which KDD has led the world in the exchange of theoretical research and practical experiences in the field of knowledge discovery and data mining.The KDD-2004 technical program features two parallel research tracks and an industrial/government track. The program also features keynote addresses by Eric Hazeltine and David Heckerman, eight workshops, six tutorials, and two panels. The 2004 KDD Cup competition focuses on supervised classification tasks in the analysis of two datasets in particle physics and bioinformatics. Exhibits from vendors and other organizations complement the program and underscore the breadth and impact of our field.Once again we have received a record number of submissions, and the selection process was extremely competitive. Each paper was independently reviewed by at least three members of the program committee for originality, significance, technical quality and clarity of presentation. This was followed by discussion among the reviewers and final decisions. Of the 337 research track submissions received, 40 were accepted as full papers for oral presentation, and 45 were accepted for poster presentation (12% and 13% of submissions, respectively). The industrial/government track received 47 submissions, of which 14 were accepted for oral presentation and 13 were accepted for poster presentation (30% and 28%, respectively).The resulting program is diverse and exciting. Topics include classification, clustering, frequent itemsets, scalability, Bayesian methods, graph and network analysis, dimensionality reduction, methods for spatial and temporal data, privacy preserving data mining, and many others. Application areas include astronomy, web text mining, microeconomics, spam and virus detection, medicine and genetics, and many others.A conference like KDD-2004 would not be possible without the dedicated effort of many individuals. In particular, we thank: the industrial/government track chairs, R. Bharat Rao and John Elder, and all the function chairs, for all their hard work putting together the multiple elements of the conference; the members of the program committee, the industrial/government track program committee, and the best paper awards committee, for their efforts reviewing and discussing papers; Won Kim and the SIGKDD Executive Committee, for their guidance and support; Jessica Wilmers and other ACM staff for their logistical support; Stacey Shirk at Cornell for administrative support, and the Microsoft CMT team, for providing the software and technical assistance to run the reviewing process. In addition to these individuals, we would like to thank Teresa Mah who helped with local arrangements, and Marina Meila who volunteered to lead the day trip to Rainer National Park.