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PAKDD 2009 : 13th Pacific-Asia Conference on Knowledge Discovery and Data Mining

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Link: http://itpe.siit.tu.ac.th/pakdd/
 
When Apr 27, 2009 - Apr 30, 2009
Where Bangkok
Abstract Registration Due Sep 16, 2008
Submission Deadline Sep 23, 2008
Notification Due Dec 8, 2008
Final Version Due Jan 9, 2009
Categories    data mining   machine learning   artificial intelligence
 

Call For Papers

The 13th Pacific-Asia Conference on Knowledge Discovery and Data Mining
(PAKDD-09) is a major international conference in the areas of data mining and knowledge
discovery. It provides an international forum for researchers and industry practitioners to share their new ideas, original research results and practical development experiences from all
KDD-related areas including data mining, data warehousing, machine learning, databases,
statistics, knowledge acquisition and automatic scientific discovery, data visualization, causal induction and knowledge-based systems.
The conference calls for research papers reporting original investigation results and industrial
track papers reporting real data mining applications and system development experience.
A. Data Mining Foundations
A1. eoretic Foundations
A2. Novel Algorithm
A3. Association Rules
A4. Classification and Ranking
A5. Clustering
A6. Text Mining
A7. Machine Learning
A8. Privacy Preserving Data Minig
A9. Statistical Methods
A10. Parallel and Distributed Data Mining
A11. Interactive and Online Mining
A12 .KDD Process and Human Interaction
A13. Knowledge Management
A14. Data and Knowledge Visualization
B. Data Mining in Specialized Domain
B1. High Dimensional Data
B2. Temporal Data
B3. Biomedical Domains
B4. Dynamic Data Mining
B5. Scientific Databases
B6. Semi-structured/unstructured Data
B7. Multimedia
B8. Reliability and Robustness Issues
B9. Integrated Media
B10. Security and Intrusion Detection
B11. Web Data and the Internet
B12. Mining Trends, Opportunities or Risks
B13. OLAP and Data Mining
B14. Integration of Data Warehousing
B15. Graphic Model Discovery
B16. Software Warehouse and Software Mining

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