Call for Papers

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In the last decade, data mining has emerged as one of most vivacious areas in information technology. Although many algorithms and techniques for data mining have been proposed, it still remains an open problem to successfully apply them to discovery actionable knowledge in real-life applications in various domains.

The workshop welcomes theoretical and applied disseminations that make efforts: (1) to design next-generation data mining methodology for actionable knowledge discovery and identify how KDD techniques can better contribute to critical domain problems in theory and practice; (2) to devise domain-driven data mining techniques to strengthen business intelligence in complex enterprise applications; (3) to present the applications of domain-driven data mining and demonstrate how KDD can be effectively deployed to solve complex practical problems; and (4) to identify challenges and future directions for data mining research and development in the dialogue between academia and industry.

Topics of Interest This workshop solicits original theoretical and practical research on the following topics.

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Domain driven KDD methodology, framework, system, infrastructure, and project management,

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Domain driven data mining technologies and algorithms,

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Domain specific KDD process and data mining techniques,

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Involvement and integration of human intelligence, domain intelligence, domain constraints and network intelligence in data mining process,

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Formalization of domain knowledge, domain constraints and domain intelligence,

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Modelling human intelligence, user preference, dynamic supervision and human-mining interaction,

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Knowledge actionability/dependability/operationability, and the integration of technical and business interestingness, and

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Reliability, trust, privacy, utility and other organizational and social issues in domain specific data mining.

 

Researchers interested in semantic-based data mining may want to submit their papers to ICDM'08 workshop on Semantic Aspects in Data Mining (SADM'08).