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Knowledge discovery in Chinese medicine
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Source C3S2E; Vol. 290 archive
Proceedings of the 2008 C3S2E conference table of contents
Montreal, Quebec, Canada
POSTER SESSION: Posters table of contents
Pages: 113 - 116  
Year of Publication: 2008
ISBN:978-1-60558-101-9
Authors
Tongyuan Wang  Concordia University, Montreal, Canada
Bipin C. Desai  Concordia University, Montreal, Canada
Huzhan Zheng  Beijing University of Chinese Medicine, Beijing, China
Yanjiang Qiao  Beijing University of Chinese Medicine, Beijing, China
Sponsors
: ACM International Conference Proceedings Series
Concordia University : Concordia University
: BytePress
Publisher
ACM  New York, NY, USA
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ABSTRACT

Our motivation for knowledge discovery in Chinese medicine is two folds: innovate and verify effective data mining technology in realistic applications; and update Chinese medical informatics. This paper focuses on the former aspect. To develop effective mining functions for Chinese medicine study, we have considered a number of critical issues including: data complications, mining model reliability, and mining tools' usability. The result is a fuzzy based "Hyper Knowledge Discovery System" (HKDS). This paper presents our recently proposed concepts and approaches as well as their flexibility and interactivity in information retrieval and association rule mining embodied in HKDS.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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Q. Yang, X. Wu, "10 Challenging Problems in Data Mining Research". International Journal of Information Technology & Decision Making, Vol. 5, No. 4 (2006) 597--604. World Scientific Publishing Company, 2006.
 
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K. L. Ong, W. K. Ng, E. P. Lim, "Mining Multi-Level Rules with Recurrent Items Using FP'-Tree," 3rd IEEE International Conference on Information, Communications and Signal Processing (ICICS'2001), 2001.
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Collaborative Colleagues:
Tongyuan Wang: colleagues
Bipin C. Desai: colleagues
Huzhan Zheng: colleagues
Yanjiang Qiao: colleagues