Data Mining Topics of Interest

Topics include, but are not limited to, the following:

Data Mining Tasks

Regression/Classification
Time series forecasting
Segmentation/Clustering/Association
Deviation and outlier detection
Explorative and visual data mining
Web mining
Text mining
Mining semi-structured data
Temporal and spatial data mining
Multimedia mining (audio/video)
Others

Data Mining Algorithms

Artificial neural networks
Fuzzy logic and rough sets
Decision trees/rule learners
Support vector machines
Evolutionary computation/meta heuristics
Statistical methods
Collaborative filtering
Case based reasoning
Link and sequence analysis
Ensembles/committee approaches
Others

Data Mining Integration

Mining large scale data
Distributed data mining
grid based data mining
Data & knowledge representation
Data warehousing
OLAP integration
Integration of prior knowledge
Integration of domain knowledge
Metadata and ontologies
Agent technology for data mining
Legal aspects of data mining
Social aspects of data mining
Others

Data Mining Process

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Data cleaning and preparation
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Feature selection and transformation
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Attribute discretisation and encoding 
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Sampling and rebalancing
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Missing value imputation
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Model selection/assessment 
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Model comparison
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Induction principles
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Model interpretation
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Others
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Data Mining Applications

Bioinformatics
Medicine Data Mining
Business Data Mining
Corporate Data Mining
Credit Scoring
Direct Marketing
Database Marketing
Industrial Data Mining
Engineering Mining
Military Data Mining
Security Data Mining
Social science Mining
Others

We particularly encourage submissions of industrial applications and case studies from practitioners. These will not be evaluated using solely theoretical research criteria, but will take general interest and presentation stringer into consideration.

Data Mining Software

All aspects & modules

Alternative & additional examples of possible topics include:

Data Mining for Business Intelligence
Emerging technologies in data mining
Computational performance issues in data mining
Data mining in usability
Advanced prediction modelling using data mining
Data mining and national security
Data mining tools
Data analysis
Data preparation techniques (selection, transformation, and preprocessing)
Information extraction methodologies
Clustering algorithms used in data mining
Genetic algorithms and categorization techniques used in data mining
Data and information integration
Microarray design and analysis
Privacy-preserving data mining
Active data mining
Statistical methods used in data mining
Multidimensional data
Case studies and prototypes
Automatic data cleaning
Data visualization
Theory and practice - knowledge representation and discovery
Knowledge Discovery in Databases (KDD)
Uncertainty management
Data reduction methods
Data engineering
Content mining
Indexing schemes
Information retrieval
Metadata use and management
Multidimensional query languages and query optimization
Multimedia information systems
Search engine query processing
Pattern mining
Applications (examples: data mining in education, marketing, finance and financial services, business applications, medicine, bioinformatics, biological sciences, science and technology, industry and government, ...)

FAQ - Frequent Questions

Can I also submit papers on other topics?

Yes, but the topic should be somewhat related to the methods, applications, processes or future extensions of data mining. We particularly welcome all papers on methods of Artificial Intelligence, Computational Intelligence, Machine Learning etc. If in doubt, please contact the programme chair beforehand.

Contact

Robert Stahlbock
General Conference Chair

E-mail: conference-chair@dmin--2009.com

Sven F. Crone

Programme Chair

E-mail: programme-chair@dmin--2009.com

This website is hosted by the Lancaster Centre for Forecasting at the Department of Management Science at Lancaster University Management School.