Dynamic learning and knowledge representation for data mining

Details Dynamic learning and knowledge representation for data mining Dynamic learning and knowledge representation for data mining

2006-06-16

2009-08-11

Fleurantin, Jean B. (Department: 2162)

Data processing: database and file management or data structures

Database design

Data structure types

C707S793000

Reexamination Certificate

active

07574454

ABSTRACT:
An integrated human and computer interactive data mining method receives an input database. A learning, modeling, and analysis method uses the database to create an initial knowledge model. A query of the initial knowledge model is performed using a query request. The initial knowledge model is processed to create a knowledge presentation output for visualization. It further comprises a feedback and update request step that updates the initial knowledge model.A multiple level integrated human and computer interactive data mining method facilitates overview interactive data mining and dynamic learning and knowledge representation by using the initial knowledge model and the database to create and update a presentable knowledge model. It facilitates zoom and filter interactive data mining and dynamic learning and knowledge representation by using the presentable knowledge model and the database to create and update the presentable knowledge model. It further facilitates details-on-demand interactive data mining and dynamic learning and knowledge representation by using the presentable knowledge model and the database to create and update the presentable knowledge model.The integrated human and computer interactive data mining method allows rule viewing by a parallel coordinate visualization technique that maps a multiple dimensional space onto two display dimensions with data items presented as polygonal lines.

REFERENCES:
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Keim, Daniel et al., “Information Visualization and Visual Data Mining”, IEE Transactions on Visualization and Computer Graphics,vol. 8. No. 1, p. 1-8 [online] Jan. 2002. Retrieved from the Internet:<URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=981847&isnumber=21152>.
Chi,Ed H. et. al., “A taxonomy of visualization techniques using the data statereference model”, Proceedings of the IEEE Symposium on Information Visualization, P-69-75 [online] Oct. 2000. Retrieved from the Internet:<URL: http://ieeexplore.ieee.org /stamp/stamp.jsp?tp=&arnumber=885092&isnumber=19138>.

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