CONFERENCES & SEMINARS FOR 00/02/15

Feb 15, Mar 2, Mar 3, Mar 22, 2000
CLOSING THE E-COMMERCE GAP
Locations: San Francisco, CA; Chicago, IL; Boston, MA; Houston, TX
Contact: www.acta.com.

Feb 22, 2000
TDWI FIFTH ANNUAL IMPLEMENTATION CONFERENCE
Location: Anaheim, CA
Contact: Melissa Crowe (508) 366-3888 x3796

Feb 29 - Mar 1, 2000
IT OUTSOURCING CONFERENCE
Location: San Diego, CA
Contact: 978-470-3880

Feb 29 - Mar 2, 2000
INTERNET & ELECTRONIC COMMERCE CONFERENCE
Location: New York City, NY
Contact: www.iec-expo.com

Apr 10-13, 2000
ICDCS INTERNATIONAL WORKSHOP OF KNOWLEDGE DISCOVERY & DATA MINING IN THE WORLD-WIDE WEB
Location: Taipei, Taiwan, ROC
Contact: www.ee.ntu.edu.tw/~mschen/workshop/cfp.htm

Apr 18-20, 2000
FOURTH PACIFIC-ASIA CONFERENCE ON KNOWLEDGE DISCOVERY AND DATA MINING
Location: Kyoto, Japan
Contact: www.keihanna-plaza.co.jp/pakdd00/

May 5, 2000
THIRD WORKSHOP ON HIGH PERFORMANCE DATA MINING
Location: Cancun, Mexico
Contact: www.cs.rpi.edu/~zaki/HPDM/
Description:

The 3rd WORKSHOP ON HIGH PERFORMANCE DATA MINING
Friday, May 5th, 2000, Cancun, Mexico
with Int'l Parallel and Distributed Processing Symposium (IPDPS'00)
(the new name for the merged IPPS and SPDP conferences)

The explosive growth in data collection in business and scientific fields has literally forced upon us the need to analyze and mine useful knowledge from it. Data mining refers to the entire process of extracting useful and novel patterns/models from large datasets. Due to the huge size of data and amount of computation involved in data mining, high-performance computing is an essential component for any successful large-scale data mining application. This workshop will provide a forum for presenting recent results in high-performance computing for data mining including applications, algorithms, software, and systems. High-performance should be broadly interpreted as including scalable sequential as well as parallel and distributed algorithms and systems.

Workshop proceedings will be published as a volume in Springer-Verlag's LNCS series. For up-to-date information on this workshop, please see www.cs.rpi.edu/~zaki/HPDM/.

IMPORTANT DATES

• Papers Due: December 1st, 1999
• Acceptance Notification: January 17, 2000
• Camera Ready Papers Due: January 28, 2000

WORKSHOP CHAIRS

• Vipin Kumar, University of Minnesota, kumar@cs.umn.edu
• David Skillicorn, Queens University, Canada, skill@cs.queensu.ca
• Mohammed J. Zaki, Rensselaer Polytechnic Institute, zaki@cs.rpi.edu

July 5-7, 2000
SECOND INTERNATIONAL CONFERENCE ON DATA MINING
Location: Cambridge, UK
Contact: www.wessex.ac.uk
Description: Organised by Wessex Institute of Technology, UK

OBJECTIVES

Data mining is a promising and relatively new area of current research and development which can provide important advantages to the users. It can yield substantial knowledge from data primarily gathered for a wide range of quite different applications. Financial institutions have derived considerable benefits from its application and other industries and disciplines are now applying the methodology to increasing effect.

The second International Conference on Data Mining will provide an international forum for the sharing of original research results and practical development experiences among researchers and applications developers from different areas such as computer experts, statisticians, knowledge acquisition specialists, data analysts, IT consultants, data visualisation experts, and users and developers in business and industry.

The Conference aims to bring together the participants from academic and research, industry and government organisations. The meeting will allow participants to learn about the many different applications of data mining and how the techniques can help in their own field.

TOPIC CATEGORIES

• Applications of Data Mining in Science, Engineering, Business,Industry, Medicine
• Data Warehousing and Databases
• Internet Applications
• Fraud Detection and Prevention
• Data Mining as a Tool for Marketing and Sales Support
• Managing Data Mining Projects
• Data Mining Software
• Data Discovery
• Data Mining Methodologies
• Knowledge Discovery and Data Mining
• Multi-database Mining
• Machine Learning Methods
• Neural Networks and Decision Trees
• Genetic Algorithms in Data Mining
• Parallel and Distributed Techniques
• Market Basket Analysis
• Visualisation in Data Mining
• Statistically Based Tools
• Clustering and Classification Techniques
• Tools for Pattern Discovery
• Prediction of Future Trends with Historical Data Case Studies

Please forward all relevant conference listings to dseditor@dsstar.com.