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Megaputer exhibits at the Eighth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD-2002)
KDD-2002 Website Edmonton, Alberta, Canada The continuing rapid growth of on-line data and the widespread use of databases have created a need and an opportunity for extracting useful knowledge from databases and making database access easier and more convenient. This conference will bring together researchers and practitioners and focus on new developments in Knowledge Discovery and Data Mining. The challenge of extracting knowledge from data is an are of common interest to researchers in several fields, including statistics, databases, pattern recognition, machine learning, data visualization, optimization and high-performance computing. The Eighth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD-2002) will follow on the success of previous KDD conferences.
JSM (the Joint Statistical Meetings) is the largest gathering of statisticians held in North America. It is held jointly with the American Statistical Association, The International Biometric Society (ENAR and WNAR), the Institute of Mathematical Statistics, and the Statistical Society of Canada. Attended by over 4000 people, activities of the meeting include oral presentations, panel sessions, poster presentations, continuing education courses, exhibits of state-of-the-art statistical products and opportunities, a placement service, society and section business meetings, committee meetings, social activities, and networking opportunities. Date: August 5-9, 2001 Location: Atlanta, GA Details: Megaputer exhibits in the booth # 403 Website: Joint Statistical Meetings Website
We live in the Age of Information. The importance of collecting data that reflect your business or scientific activities to achieve competitive advantage is widely recognised now. Powerful systems for collecting data and managing it in large databases are in place in all large and mid-range companies. However, the bottleneck of turning this data into your success is the difficulty of extracting knowledge about the system you study from the collected data. What goods should be promoted to this customer? What is the probability that a certain customer will respond to a planned promotion? Can one predict the most profitable securities to buy/sell during the next trading session? Will this customer default on a loan or pay back on schedule? What medical diagnosis should be assigned to this patient? How large the peak loads of a telephone or energy network are going to be? Why the facility suddenly starts to…