ICDMA 2012 - IAENG International Conference on Data Mining and Applications (ICDMA'12)

The IAENG International Conference on Data Mining and Applications (ICDMA'12) will take place in Hong Kong, 14-16 March, 2012.




The conference ICDMA'12 is held under the International MultiConference of Engineers and Computer Scientists 2012. The IMECS 2012 is organized by the International Association of Engineers (IAENG), a non-profit international association for the engineers and the computer scientists. The IMECS conferences serve as good platforms for our members and the entire engineering community to meet with each other and to exchange ideas. Our IMECS committees have been formed with over three hundred conference committees members who are mainly research center heads, faculty deans, department heads, professors, and research scientists from over 30 countries. The last IMECS 2011 has attracted more than eight hundred participants from over 50 countries. All submitted papers will be under peer review and accepted papers will be published in the conference proceeding (ISBN: 978-988-19251-1-4). The abstracts will be indexed and available at major academic databases. The accepted papers will also be considered for publication in the special issues of the journal Engineering Letters, in IAENG journals and in edited books.



Calls for Manuscript Submissions



Important Dates:

Draft Manuscript submission deadline: 8 December, 2011

Camera-Ready Papers Due & Registration Deadline: 10 January, 2012

IMECS 2012: 14-16 March, 2012




The topics of the ICDMA'12 include, but not limited to, the following:




Soft Computing Data Mining Tools:
Artificial intelligence
Artificial neural network
Fuzzy logic
Automatic Learning Data Mining Tools:
Machine learning
Nearest neighbor (pattern recognition)
Pattern recognition

Statistical Data Mining Tools:
Hypothesis testing
Linear discriminant analysis
Logistic regression
Principal components analysis
Regression analysis


Data Mining Applications:
Business intelligence
Business performance management
Database
Data stream mining
Data warehouse
Decision tree
Descriptive statistics
Document warehouse
Relational data mining
Text mining