CFPFrom: Mohammed Zaki zaki@badr.cs.rpi.eduDate: Mon, 9 Oct 2000 14:05:43 -0400 Subject: CFP: Workshop on Parallel and Distributed Data Mining, San Francisco, CA, USA, April 23-27, 2001 WORKSHOP CHAIRS: Mohammed J. Zaki, Rensselaer Polytechnic Institute (zaki@cs.rpi.edu) Vipin Kumar, University of Minnesota (kumar@cs.umn.edu) David Skillicorn, Queens University, Canada (skill@cs.queensu.ca) URL: http://www.cs.rpi.edu/~zaki/PDDM01/ WORKSHOP HISTORY: This is the 4th workshop on this theme held annually in conjunction with the IPDPS conference. The first three workshops went under the name "High Performance Data Mining," and were held at Orlando ( HPDM'98), San Juan ( HPDM'99) and Cancun ( HPDM'00). In keeping with the growing popularity and international scope of this field, this workshop has been renamed "International Workshop on Parallel and Distributed Data Mining". This year we hope to attract even more high quality papers, and look forward to increased participation from both academia and industry. DESCRIPTION: As the volume of data increases, it is clear that both parallel and distributed data mining techniques are required to make the whole knowledge discovery process scalable and interactive. This workshop will target papers on high performance parallel and distributed methods, as well as mining on distributed and heterogeneous datasets. Topics of interest include: * Efficient, scalable, disk-based, parallel and distributed algorithms for large-scale data mining tasks. * New algorithms for common data mining methods such as association rules, sequences, classification, clustering, deviation detection, etc. * Pre-processing and post-processing operations like sampling, feature selection, data reduction and transformation, rule grouping and pruning, etc. * Incremental, exploratory and interactive mining * Meta-mining, coping with distributed and/or heterogeneous datasets. * Integration of mining with parallel/distributed databases and datawarehouses. * Mining non-traditional datasets, such as large scientific databases. * Frameworks for KDD systems, and parallel or distributed mining. * Agent based approaches for PDDM. * Applications of PDDM in business, science, engineering, medicine, and other disciplines. * Theoretical foundation of PDDM. IMPORTANT DATES: NOVEMBER 15, 2000: Submissions Due January 5, 2001: Acceptance Notification January 22:Camera Ready Copy Due |
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