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Data Mining Topics of Interest
Topics include, but are not limited to, the
following:
Data Mining
Tasks
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Regression/Classification
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Time series forecasting
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Segmentation/Clustering/Association
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Deviation and outlier detection
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Explorative and visual data mining
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Web mining
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Text mining
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Mining semi-structured data
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Temporal and spatial data mining
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Multimedia mining (audio/video)
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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
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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
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
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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, ...)
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FAQ -
Frequent Questions
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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. |
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