Difference between revisions of "ECML PKDD 2009"
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The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases provides an international forum for the discussion of the latest high quality research results in all areas related to machine learning and knowledge discovery in databases. Encouraged are submissions of papers that describe the application of machine learning and data mining methods to real-world problems, particularly exploratory research that describes novel learning and mining tasks and applications requiring non-standard techniques. Submissions that demonstrate both theoretical and empirical rigor are especially encouraged. | The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases provides an international forum for the discussion of the latest high quality research results in all areas related to machine learning and knowledge discovery in databases. Encouraged are submissions of papers that describe the application of machine learning and data mining methods to real-world problems, particularly exploratory research that describes novel learning and mining tasks and applications requiring non-standard techniques. Submissions that demonstrate both theoretical and empirical rigor are especially encouraged. | ||
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Revision as of 20:32, 14 October 2008
| ECML PKDD 2009 | |
|---|---|
The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases
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| Dates | Sep 7, 2009 (iCal) - Sep 11, 2009 |
| Homepage: | www.ecmlpkdd2009.net/ |
| Location | |
| Location: | Bled, Slovenia |
| Important dates | |
| Submissions: | Apr 20, 2009 |
| Notification: | Jun 10, 2009 |
| Camera ready due: | Jun 20, 2009 |
| Table of Contents | |
The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases provides an international forum for the discussion of the latest high quality research results in all areas related to machine learning and knowledge discovery in databases. Encouraged are submissions of papers that describe the application of machine learning and data mining methods to real-world problems, particularly exploratory research that describes novel learning and mining tasks and applications requiring non-standard techniques. Submissions that demonstrate both theoretical and empirical rigor are especially encouraged.