Topics:

The 1st PAKDD Doctoral Symposium on Data Mining (DSDM’11) calls for research papers reporting original investigation results, real-world applications and system development experience, in all aspects of data mining. The topics of the DSDM’11 papers fall into two major categories which will include but are not limited to the following:
A. Data Mining Foundations
A1. Theoretic Foundations
A2. Novel Models and Algorithms
A3. Statistical Methods
A4. Association Rules
A5. Classification and Ranking
A6. Clustering
A7. Robust and Highly Scalable Data Mining Algorithms
A8. Privacy Preserving Data Mining
A9. Parallel and Distributed Data Mining
A10. Interactive and Online Mining
A11. Pre-processing and Post-processing in Data Mining
A12. Knowledge Management
A13. Data and Knowledge Visualization
B. Data Mining in Specialized Domain
B1. High Dimensional Data
B2. Imbalanced Data
B3. Spatial and Temporal Data
B4. Stream Data
B5. Graph Data
B6. Uncertain and Probabilistic Data
B7. Semi-Structured/Unstructured Data
B8. Biological and Medical Data
B9. Software Engineering Data
B10. Scientific Data
B11. Financial Data
B12. Multimedia Data
B13. Web Data and the Internet
B14. Security and Intrusion Detection
B15. Mining Social Networks
B16. Mining Trends, Opportunities or Risks
B17. Mining with Auxiliary Data Sources


Publication and Paper Submission:

Accepted papers will be published in the PAKDD’11 workshop proceedings of LNCS series

Each paper should consist of a cover page with title, authors’ names, postal and email address, an up to 200-words abstract, up to 5 keywords and a body no longer than 12 single-spaced pages with font size at least 11 pts. Authors are strongly encouraged to use Springer’s manuscript submission guidelines for their initial submissions. All papers must be submitted electronically in PDF format only, using the conference management tool. Please make sure that any special fonts used are included in the submitted documents. The submitted papers must not be published or under consideration to be published elsewhere.