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KDD-2008 Conference Goes Beyond Data

Data Mining Experts Explore Latest Advances in Social Networks, Medical Data Mining, Search Applications in Commerce

The Association for Computing Machinery
Advancing Computing as a Science & Profession

Contact: Virginia Gold

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Las Vegas, August 20, 2008 – The KDD-2008 Conference, hosted by ACM’s Special Interest Group on Knowledge Discovery and Data Mining (SIGKDD), will present recent developments in the rapidly evolving field of data mining and knowledge discovery. The 14th annual KDD conference combines hot research topics and important industrial applications in key areas like social networks, text and graph mining, recommender systems that filter information of interest to the user (i.e. Netflix), medical data mining and visual analytics. KDD-2008, the leading forum for data mining researchers and practitioners, will take place August 24-27, at the Loews Lake Las Vegas Resort, in Henderson, NV.

Program highlights include renowned experts in the data mining field. Among the speakers are:

  • Trevor Hastie of Stanford University on “Regularization Paths and Coordinate Descent” - August 25
  • Thore Graepel of Microsoft Research on “Large Scale Data Analysis and Modeling in Online Services and Advertising” - August 25
  • Michael Schwarz of Yahoo! Research on “Internet Advertising and Optimal Auction Design” - August 26
  • Udo Miletzki of Siemens AG on “The Genesis of Postal OCR and Beyond” - Tuesday, August 26
  • Jitendra Malik of the University of California Berkeley on “The Future of Image Search” - August 27

This year, the prestigious KDD Cup – the oldest data mining competition – has focused on the early detection of breast cancer from X-ray images of the breast based on data provided by Siemens Medical Solutions USA. The KDD Cup winners will describe their work in the KDD Cup workshop on Sunday, August 24.

The KDD-2008 also features keynote presentations, oral paper presentations, poster sessions, workshops, tutorials, panels, exhibits, and demonstrations. Among the tutorial topics are: challenges of mining moving-object data; predictive modeling for social networks; state-of-the-art methods of mining uncertain and probabilistic data; how to find clusters in moderate- to high-dimensional data; a case study of identifying influential bloggers in a community; and solving information overload through text-mining.

A highlight of conference is the announcement of the ACM SIGKDD Innovation Award recipient. This is the highest technical award in the field of data mining and knowledge discovery. New this year is the KDD Dissertation Award, to be presented to the best young Ph.D. student in the data mining and knowledge discovery field.

For more information and to register, click on


SIGKDD ACM’s Special Interest Group on Knowledge Discovery and Data Mining, is the major professional organization for data mining and knowledge discovery researchers and professionals, focusing on the advancement of the science and practice of knowledge discovery and data mining.

About ACM

ACM, the Association for Computing Machinery, is the world’s largest educational and scientific computing society, uniting computing educators, researchers and professionals to inspire dialogue, share resources and address the field’s challenges. ACM strengthens the computing profession’s collective voice through strong leadership, promotion of the highest standards, and recognition of technical excellence. ACM supports the professional growth of its members by providing opportunities for life-long learning, career development, and professional networking.