CFP

PAKDD 2003 Workshop
INTERNATIONAL WORKSHOP ON DATA MINING FOR ACTIONABLE KNOWLEDGE
(DMAK'2003)
Seoul, Korea, April 30 2003

Web: http://dmak.hanyang.ac.kr

Theme

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.

For Topics of Interest and Submission instructions, see the website.
Important Dates:
Workshop paper submission deadline -- Jan 20, 2003
Workshop paper notification -- Feb 20, 2003
Camera ready copy due -- March 1, 2003


Workshop Organisers

Youjip Won, Hanyang University, Korea
yjwon@ece.hanyang.ac.kr

San-Yih Hwang, National Sun Yat-Sen University, Taiwan
syhwang@mis.nsysu.edu.tw

Ee-Peng Lim, Nanyang Technological University, Singapore
aseplim@ntu.edu.sg