1. H.-D.
Jin, M.-L. Wong, and K.-S. Leung, “Scalable Model-based Clustering for
Large Databases Based on Data Summarization,” IEEE Transactions on
Pattern Analysis and Machine Intelligence, vol. 27, no 11, pp. 1710-1719,
Nov. 2005.
2. H.-D Jin, J. Chen, H. He, G. Williams, C. Kelman and
C.M. O'Keefe. "Mining
Unexpected Temporal Associations:." IEEE Transactions on Information Technology
in Biomedicine (In press, May 2007).
3. H.-D. Jin, K.-S.
Leung, M.-L. Wong, and Z.-B. Xu,
"Scalable Model-based Cluster
Analysis Using Clustering Features," Pattern Recognition,
vol. 38, no 5, pp.637-649, May 2005.
4. K.-S. Leung, H.-D. Jin, Z.-B. Xu, "An expanding self-organizing neural
network for the traveling salesman problem,"
Neurocomputing, vol. 62, pp 267-292,
Dec. 2004.
5. H.-D. Jin, W.-H. Shum,
K.-S. Leung, and M.-L. Wong, "Expanding Self-organizing Map for Data
Visualization and Cluster Analysis," Information Sciences, vol.
163, no 1-3, pp.157-173, June 2004.
6. H.-D. Jin, K.-S.
Leung, M.-L. Wong, and Z.-B. Xu,
"An Efficient Self-Organizing Map
Designed by Genetic Algorithms for the Traveling
Salesman Problem," IEEE Transactions on System, Man, and
Cybernetics - Part B: Cybernetics, vol. 33, no 6, pp 877-888, Dec. 2003.
7.
Z.-B.
Xu, H.-D. Jin, K.-S. Leung, Y. Leung, and C.K.
Wong, "An Automata Network for Performing
Combinatorial Optimization," Neurocomputing,
vol. 47, no 1-4, pp.59-83, 2002.
8. J. Chen, H.-D. Jin, H. He, C.M. O’Keefe,
R. Sparks, G. Williams, D. McAullay and C. Kelman. “Frequency-based Rare Events
Mining in Administrative Health Data,” Electronic Journal of Health
Informatics, Vol 1, No 1, e4, 2006.
Theses
1. H.-D. Jin, "Scalable Model-based Clustering Algorithms for
Large Databases and Their Applications," Ph.D. Dissertation,
the Chinese University of Hong Kong, Shatin, Hong
Kong, Aug. 2002. UMI ProQuest press.
2. H.-D. Jin, "An
Automata Network for Performing Combinatorial Optimization," Master Thesis, Xi'an Jiaotong University,
Xi'an, P.R.
China, Apr. 1998 (In Chinese. Its English part pdf is
available.).
Book chapters
1. J.
Chen, H. He, H. Jin, D. McAullay, G. Williams, and C. Kelman.
“Identifying Risk
Groups Associated with Colorectal Cancer,” in G.J. Williams and S.J. Simoff (Eds.), Data
Mining: Theory, Methodology, Techniques, and Applications. Springer
Berlin/Heidelberg, pp. 260 – 272, 2006.
2. H. Jin, K.-S.
Leung and M.-L. Wong, “An
Integrated Self-Organizing Map for the Traveling
Salesman Problem”, in Nikos Mastorakis (Eds). Advances in Neural Networks and Applications,
World Scientific and Engineering Society Press, pp. 235- 240, 2001
Referred Conference publication (“[ ]” indicates a student
under supervision)
1.
H.-D. Jin, J. Chen, H. He, and C.M. O'Keefe. "Privacy-Preserving Sequential Pattern
Release," The 11th
Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD’07,
paper acceptance rate 17.3%), pp. 547-554, Nanjing, China,
May 2007.
2. [B.
Jiang], H. Jin, N. Liu, M. Quirk and
B. Searle. “A HMM Based
Hierarchical Framework for Long-term Population Projection of Small Areas,”
AI 2007. Accepted Sep 2007.
3. [Y. Lu],
H. Gardner, H. Jin, N. Liu, Rhys
Hawkins and I. Farrington. “Interactive Reconstruction of
Archaeological Fragments in a Collaborative Environment.” DICTA’07. Accepted in Sep 2007.
4.
[K. Zhang], H. Jin, Z. Fu and N.
Liu. “Optimal Learning
High-order MRF Priors for Color Image Denoising,” ACCV’07.
Accepted Aug 2007.
5.
H. Jin, Olivier de Vel and N. Liu. “Knowledge
Discovery from Honeypot Data via Clustering.” RAID’07. 2007 (a poster accepted in July)
6.
H.-D. Jin, “Practical
Issues on Privacy-Preserving Health Data Mining,” Working Notes of PAKDD’07 Industrial
Track (Regular paper acceptance rate 18.3%), pp 130-140. Nanjing, China,
May 2007.
7.
[K. Zhang],
H.-D. Jin, N. Liu, R. Lesslie, L. Wang, Z. Fu and T. Caelli. “Discovering Prediction Model for
Environment Distribution Maps,” Working
Notes of PAKDD’07 Industrial Track (Regular paper acceptance rate
18.3%), pp 61-71. Nanjing, China, May 2007.
8.
H. Jin, J. Chen, C. Kelman, H. He, D. McAullay, and C.M. O'Keefe. “Mining Unexpected Associations for
Signalling Potential Adverse Drug Reactions from Administrative Health
Databases.” The Tenth
Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD2006,
regular paper acceptance rate 13.4%), pp. 867-876, Singapore, April, 2006.
9. H.
He, H.-D. Jin, J. Chen, D. McAullay, J. Li and T. Fallon. “Analysis of Breast Feeding Data Using Data Mining Methods,”
Proceedings of Australasian Data Mining
Conference, pp 47-52, Sydney,
Nov. 2006.
10. J. Li, H. Wang, H.-D. Jin and J. Yong. “Current developments of k-Anonymous data releasing,”
in: P. Croll, H. Morarji
and R. Au (Ed.). Proceedings of
the National e-Health Privacy and Security Symposium, pp. 109-121. Queensland Australia, Oct 2006.
11. H.
He, J. Chen, H. Jin, and Shuheng Chen. “Stock Trend
Analysis and Trading Strategy.” The 9th Joint Conference on Information Sciences, Kaohsiung, Taiwan,
ROC, Oct. 2006.
12.
H. He, H.-D.
Jin, and J. Chen. “Automatic feature selections in medical data
classification,” the 18th Australian Joint Conference on Artificial Intelligence (AI 2005), Sydney, Australia, Dec. 2005.
13. J. Li, A.
Fu, H. He, J. Chen, H.-D. Jin, D. McAullay,
G. Williams, R. Sparks and C. Kelman.
"Mining Risk Patterns in
Medical Data," Proceedings
of the Eleventh ACM SIGKDD International Conference on Knowledge Discovery and
Data Mining (SIGKDD'05),
pp. 770-775, Chicago,
USA, August,
2005.
14. J. Chen,
H. He, J.
Li, H.-D. Jin, D. McAullay, G.
Williams, R.
Sparks, and C. Kelman. "Representing Association,
Classification Rules Mined From Health Data." Proceedings of Knowledge-Based
and Intelligent Information & Engineering Systems
(KES 2005),
pp.1225-1231, Melbourne, Australia,
2005.
15. D. McAullay,
G. Williams, J. Chen, H.-D. Jin, H. He, R. Sparks,
and C. Kelman. “A Delivery Framework for Health Data Mining and
Analytics,” Twenty-Eighth Australasian Computer Science Conference
(ACSC2005), pp. 381-390, Newcastle, Australia,
2005.
16. J. Chen, H. He, G.
Williams, and H.-D. Jin, "Temporal
Sequence Associations for Rare Events," The Eighth Pacific-Asia
Conference on Knowledge Discovery and Data Mining (PAKDD'04), pp. 235-239, Sydney, Australia,
May 2004.
17. H.-D. Jin, M.-L. Wong, and
K.-S. Leung, "A
Scalable Model-based Clustering by Working on Data Summaries," The Third
IEEE International Conference on Data Mining (ICDM'03, regular paper
acceptance rate 11.6%), pp.91-98, Melbourne,
Florida, USA,
Nov. 2003.
18. H.-D. Jin and M.-L. Wong,
"Adaptive Diversity
Maintenance and Convergence Guarantee in Multiobjective
Evolutionary Algorithms," IEEE Congress on Evolutionary
Computation 2003 (CEC'03), pp 2498-2505, Canberra, Australia,
Dec. 2003.
19. W.-H. Shum, H.-D.
Jin, K.-S. Leung, and M.-L. Wong, "A Self-Organizing Map with Expanding Force for Data Clustering and
Visualization," Proceedings of 2002 IEEE International Conference on
Data Mining (ICDM'02, regular
paper acceptance rate: 19.6%), pp. 434-441, Maebashi City, Japan, Dec.
2002.
20. H.-D. Jin, K.-S. Leung, and
M.-L. Wong, "Scaling-up
Model-based Clustering Algorithm by Working on Clustering Features," Proceedings
of the Third International Conference on Intelligent Data Engineering and
Automated Learning (IDEAL 2002), pp. 569-575,
Manchester, UK, 2002.
21. H.-D. Jin, K.-S. Leung, and
M.-L. Wong, "A Genetic
Algorithm-guided Model-based Clustering Algorithm," Proceedings
of the International Conference on Artificial Intelligence, pp.653-659,
2001.
Paper Withdrawn
1. H. Jin, J. Chen, H. He, C. Kelman, D. McAullay, and C.M. O'Keefe. “Signalling Potential
Adverse Drug Reactions from Administrative Health Data.” KDD’07 (Accepted as a regular industrial track
paper and selected as the runner-up for Best Application Paper Award,
but withdrawn).