Motivation and scope
Data Mining algorithms present some drawbacks due to the nature of the problem they try to solve. They are very time and CPU consuming, they tend to obtain an excessive number of outputs which are unmanageable for human experts, and they must be able to deal with imprecise, uncertain and noisy data.
So it is necessary to develop techniques which might allow us to obtain good results (even though not the very best ones) in a reasonable amount of time, techniques capable to properly summarize the results obtained during the knowledge discovery process, and techniques able to manage imperfect data.
Advanced representation schemes and "Soft Computing" techniques have proved valuable when they are applied to Data Mining problems. Therefore, we encourage authors to present original papers dealing with the incorporation of these techniques into data mining algorithms and processes.
Topics
Topics of interest include, but are not limited to:
- Fuzzy techniques in Data Mining
- Rough sets in Data Mining
- Genetic algorithms in Data Mining
- Methods for dealing with imperfect information
- Uncertainty management
- Advanced techniques for knowledge representation
- Ontologies for Data Mining
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Latest News
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The workshop final program is now available, including the electronic versions of all the accepted papers.
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Workshop registration fees
| By 09/26
| After 09/26
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IEEE [CS] members
| US$130
| US$180
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Non-members
| US$180
| US$225
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Students
| US$90
| US$110
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A discount of $50 will be provided for people who also register for the main ICDM conference.
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Important dates
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Paper submission
September 8th, 2004
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Notification of acceptance
September 24th, 2004
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Camera-ready manuscripts
October 12th, 2004
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Workshop
November 1st, 2004
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