ICDM 2012 - International Conference on Data Mining (ICDM 2012)

The VIII. International Conference on Data Mining is the premier forum for the presentation of new advances and research results in the fields of Data Mining. The conference will bring together leading researchers, engineers and scientists in the domain of interest from around the world. Topics of interest for submission include, but are not limited to:

Data mining foundations
Novel data mining algorithms in traditional areas (such as classification, regression, clustering, probabilistic modeling, and association analysis)
Algorithms for new, structured, data types, such as arising in chemistry, biology, environment, and other scientific domains
Developing a unifying theory of data mining
Mining sequences and sequential data
Mining spatial and temporal datasets
Mining textual and unstructured datasets
High performance implementations of data mining algorithms

Mining in targeted application contexts
Mining high speed data streams
Mining sensor data
Distributed data mining and mining multi-agent data
Mining in networked settings: web, social and computer networks, and online communities
Data mining in electronic commerce, such as recommendation, sponsored web search, advertising, and marketing tasks

Methodological aspects and the KDD process
Data pre-processing, data reduction, feature selection, and feature transformation
Quality assessment, interestingness analysis, and post-processing
Statistical foundations for robust and scalable data mining
Handling imbalanced data
Automating the mining process and other process related issues
Dealing with cost sensitive data and loss models
Human-machine interaction and visual data mining
Security, privacy, and data integrity

Integrated KDD applications and systems
Bioinformatics, computational chemistry, geoinformatics, and other science & engineering disciplines
Computational finance, online trading, and analysis of markets
Intrusion detection, fraud prevention, and surveillance
Healthcare, epidemic modeling, and clinical research
Customer relationship management
Telecommunications, network and systems management
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