INTERNATIONAL WORKSHOP ON DATA MINING FOR ACTIONABLE KNOWLEDGE (DMAK 2003)

⊙ April 30, 2003
⊙ COEX in Seoul, Korea
⊙ http://dmak.hanyang.ac.kr


Theme
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The data mining process consists of a series of steps ranging from
data cleaning, data selection and transformation, to pattern evaluation
and visualization. With most of the research efforts focusing on the
definition of new data mining problems and the development of new data
mining algorithms, there has been less work done on making the mined
patterns or knowledge actionable. Here, the term actionable refers to
integrating data mining with the operational systems so as to bring direct
benefits (increase in profits, reduction in cost, improvement in
efficiency, etc.) to organizations and individuals.

Integration of actionable knowledge data mining with operational systems
poses many new challenges to the existing data mining approaches. Examples
of these challenges include the algorithms and systems for enabling the
integration between data gathering and data mining, between data mining and
operational system behavior, and between operational system behavior and
cost-benefit evaluation. Data or transactions have to be gathered on the
fly to be given to data mining algorithms. Data mining algorithms have to
discover knowledge in time for use in operational systems and for planning.
Operational systems have to provide means to collect user
responses/feedback in order to measure the performance of actionable
knowledge and to tune the data mining algorithms for better return.

Topics of Interest
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This workshop calls for contributions related to extracting actionable
knowledge from data. The theme is not specific to any domain area. We
invite submissions of papers that include, but are not limited to, the
following topics:

Integrating web mining with e-commerce systems
Data mining for real-time decision making
Data mining applications with dynamic input data
Mining biosequences and its visualization
Data mining for planning
Dynamic text classification and clustering
Rule-driven e-commerce system
Customer relationship management
Personalization
Operational recommendation systems
Data mining for fraud detection
Interestingness measure for actionable knowledge
Integration of data mining steps

Important Dates:
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Workshop paper submission deadline