ICDM'04 Topics of Interest
Topics related to the design, analysis and implementation of data
mining theory, systems and applications are of interest. These
include, but are not limited to the following areas:
- Foundations of data mining
- Data mining and machine learning algorithms and methods in
traditional areas (such as classification, regression, clustering,
probabilistic modeling, and association analysis), and in new
areas
- Mining text and semi-structured data, and mining temporal, spatial
and multimedia data
- Mining data streams
- Pattern recognition and trend analysis
- Collaborative filtering/personalization
- Data and knowledge representation for data mining
- Query languages and user interfaces for mining
- Complexity, efficiency, and scalability issues in data mining
- Data pre-processing, data reduction, feature selection and feature
transformation
- Post-processing of data mining results
- Statistics and probability in large-scale data mining
- Soft computing (including neural networks, fuzzy logic,
evolutionary computation, and rough sets) and uncertainty
management for data mining
- Integration of data warehousing, OLAP and data mining
- Human-machine interaction and visual data mining
- High performance and parallel/distributed data mining
- Quality assessment and interestingness metrics of data mining
results
- Security, privacy and social impact of data mining
- Data mining applications in bioinformatics, electronic commerce,
Web, intrusion detection, finance, marketing, healthcare,
telecommunications and other fields