I am leaving University of Southern Queensland to join School of Computer and Information Science of University of South Australia. Please check my contact details and my homepage at University of South Australia. Thanks.
I am a senior lecturer at the Department of Mathematics and Computing, The University of Southern Queensland,
I was research assistant and a
tutor at Griffith University, and was a lecturer at
I received my PhD degree
from Griffith University,
Office: D1.25, Toowoomba campus.
Phone: 07 4631 5548
Fax: 07 4631 5550
Email: jiuyongATusqDOTeduDOTau
Mail address:
Dr. Jiuyong Li
Department of Math and Computing
The
Toowoomba,
OLD 4350,
Jiuyong Li, Hua Wang, ARC Discovery grant (2007 – 2009), Privacy preserving data sharing in data mining environments, A$165,000.
Jiuyong Li, ARC Discovery grant (2005 – 2007), Investigation and development of robust rule discovery and classification system, A$112,514
Paul Fahey, Shane Klease, Glenda Adkins, Jiuyong Li, Janet Taylor, Ashley Plank(2006 - 2007), Investigating student retention and progression using current data, USQ Strategic Development Fund, A$13,718.
Jiuyong Li, USQ Early Career Researcher Program grant (2002 – 2003), Generating robust predictive classification rule sets.A$9,800
PC member of the 11th International Conference on CSCW in Design, 2007
General chair of Australian Data Mining Conference (AusDM), 2006
PC member for Asia Pacific Web Conference (APWeb) 2006.
PC member for Asia Pacific Web Conference (APWeb) 2005.
PC member for International Conference on Active Media Technology (AMT) 2006.
PC member of Australia Data Mining Conference (AusDM), 2005
J. Li, Robust rule based predictions, IEEE transactions on knowledge and data engineering, 18(8), 2006, 1043-1054..
J. Li, On optimal rule discovery, IEEE transactions on knowledge and data engineering, 18 (4), 2006, 460-471.
J Li, H Wang, Huidong Jin, and Jianming Yong, Current Developments of k-Anonymous Data Releasing, electronic Journal of Health Informatics, in press.
Jiuyong Li, Jason Jones, Using multiple and negative target rules to make classifier more understandable, Knowledge-based Systems, 19(6), 2006, Elsevier.
R. Wong, J. Li, A. Fu, K. Wang,
(alpha,
k)-Anonymity: An Enhanced k-Anonymity Model for Privacy-Preserving Data
Publishing, Proceedings of the twelfth ACM SIGKDD international
conference on knowledge discovery and data mining (KDD), 2006.
J. Li, R. Wong, A.Fu, J. Pei, Achieving
k-Anonymity by Clustering in Attribute Hierarchical Structures, 8th
International Conference on Data Warehousing and Knowledge Discovery, 2006.
J. Li, A. Fu, H. He, J. Chen, H. Jin, D. McAullay, G. Williams, R. Sparks, C. Kelman,
Mining risk patterns in medical data,
Proceedings of the eleventh ACM SIGKDD international conference
on knowledge discovery and data mining (KDD)，Chicago,
Illinoise, 2005,
770 - 775.
H. Hu and J, Li, Using Association Rules to Make Rule-based Classifiers Robust, Proceedings of Sixteenth Australasian Database Conference (ADC), 2005, 47 – 52, ACS Society.
J.
Chen, H. He, J. Li, H. Jin, D. McAullay, G. Williams,
R. Sparks, C. Kelman,
Representing
association classification rules mined from health data,
Knowledge Based Intelligent Systems for
Healthcare in KES2005, 1225-1231.
X. Chen, J. Li, G. Daggard, X. Huang: Finding Similar Patterns in Microarray Data. Proceedings of Australian conference on artificial intelligence (AI05), 2005, 1272-1276.
J. Li, H. Shen and R. Topor, Mining the informative rule set for prediction, Journal of Intelligent Information Systems, 22:2, 155-174, 2004, Kluwer Academic.
J. Li and Y. Zhang, Direct interesting rule generation, Proceedings of The Third IEEE International Conference on Data Mining (ICDM), 2003, Melbourne, Florida, 155 – 162, IEEE computer society.
L. Gu, J. Li, H. He, G. Williams, S. Hawkins and C. Kelman, Association rule discovery with unbalanced class distributions, Proceedings of 16th Australian Joint Conference on Artificial Intelligence, 2003, 221 – 232, Springer.
J. Li, H. Shen and R. Topor, Mining the optimal class association rule set, Knowledge-based systems, 15(7), 2002, 399 – 405, Elsevier Science.
J. Li, R. Topor and H. Shen, Construct robust rule sets for classification, Proceedings of the eighth ACMKDD international conference on knowledge discovery and data mining (KDD), 2002, 564 – 569, Edmonton, Canada.
J. Li, H. Shen and R. Topor, Mining the smallest association rule set for predictions, Proceedings of IEEE international conference on data mining (ICDM), 2001, 361 – 368, San Jose, CA.
J. Li, H. Shen and R. Topor, Mining optimal class association rule set, Proceedings of the 5th Pacific-Asia conference on methodologies for knowledge discovery and data mining (PAKDD), 2001, 364 - 375, LNAI 2035, Springer.
J. Li, H. Shen and R. Topor, An adaptive method of numerical attribute merging for quantitative association rule mining, Proceedings of the 5th international computer science conference (ICSC), 1999, 41 - 50, LNCS 1749, Springer.
More publications can be found in DBLP: Jiuyong Li
Mining
risk and preventive patterns
Robust
rule based classification
