Yanchang Zhao

PhD, MIEEE
 

This website is no longer be updated. Please click the two links below for my new websites.

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R & Data Mining: http://www.rdatamining.com

My new personal website: http://yanchang.rdatamining.com

My new contact: yanchangzhao <at> gmail.com

Research Interests

Research Grants/Projects

Work History

Selected Publications

DBLP: Yanchang Zhao

Book:

1. Longbing Cao, Philip S. Yu, Chengqi Zhang and Yanchang Zhao. "Domain Driven Data Mining". Springer. In press.

Edited Book:

1. Yanchang Zhao, Chengqi Zhang and Longbing Cao (Eds.). "Post-Mining of Association Rules: Techniques for Effective Knowledge Extraction", ISBN 978-1-60566-404-0, May 2009. 372 pages. Information Science Reference. [Book details at the publisher website]

Book Chapters:

1. Chao Luo, Yanchang Zhao, Dan Luo, Yuming Ou and Li Liu. "Recent Advances of Exception Mining in Stock Market." In Pedro Furtado (Ed.), Evolving Application Domains of Data Warehousing and Mining: Trends and Solutions, ISBN: 978-1-60566-816-1, September 2009. Information Science Reference.

2. Huaifeng Zhang, Yanchang Zhao, Longbing Cao, Chengqi Zhang, and Hans Bohlscheid. "Rare Class Association Rule Mining with Multiple Imbalanced Attributes." In Yun Sing Koh and Nathan Rountree (Eds.), Rare Association Rule Mining and Knowledge Discovery: Technologies for Infrequent and Critical Event Detection, ISBN: 978-1-60566-754-6, August 2009. Information Science Reference. pp. 66-75.

3. Paul D. McNicholas and Yanchang Zhao. "Association Rules: An Overview." In Yanchang Zhao, Chengqi Zhang and Longbing Cao (Eds.), Post-Mining of Association Rules: Techniques for Effective Knowledge Extraction, ISBN 978-1-60566-404-0, May 2009. Information Science Reference. pp. 1-10.

4. Yanchang Zhao, Longbing Cao, Huaifeng Zhang, Chengqi Zhang. "Data Clustering." In Viviana E. Ferraggine, Jorge H. Doorn and Laura C. Rivero (Eds.), Handbook of Research on Innovations in Database Technologies and Applications: Current and Future Trends, ISBN: 978-1-60566-242-8, February 2009. Information Science Reference. pp. 562-572.

5. Yanchang Zhao, Huaifeng Zhang, Longbing Cao, Hans Bohlscheid, Yuming Ou, Chengqi Zhang. "Data Mining Applications in Social Security." In Longbing Cao, Philip Yu, et al. (Eds.), Data Mining for Business Applications, ISBN 978-0-387-79419-8, Springer, 2009, pp. 81-96. [Electronic Edition]

   Journal Articles:

1. Longbing Cao, Yanchang Zhao, Huaifeng Zhang, Dan Luo and Chengqi Zhang. "Flexible Frameworks for Actionable Knowledge Discovery." Accepted by IEEE Transactions on Knowledge and Data Engineering on 21 May 2009.

2. Huaifeng Zhang, Yanchang Zhao, Longbing Cao, Chengqi Zhang and Hans Bohlscheid. "Customer Activity Sequence Classification for Debt Prevention in Social Security." Journal of Computer Science and Technology, vol. 24, no. 6, November 2009.

3. Longbing Cao, Yanchang Zhao and Chengqi Zhang. "Mining Impact-Targeted Activity Patterns in Imbalanced Data," IEEE Transactions on Knowledge and Data Engineering, vol. 20, no. 8, August 2008, pp. 1053-1066. [Electronic Edition] [BibTeX]

4. Longbing Cao, Yanchang Zhao, Chengqi Zhang and Huaifeng Zhang, "Activity Mining: from Activities to Actions," International Journal of Information Technology & Decision Making, vol. 7, issue 2, June 2008, pp. 259-273. [Electronic Edition] [BibTeX]

5. Longbing Cao, Chengqi Zhang, Yanchang Zhao, Philip S. Yu and Graham Williams. DDDM2007: Domain Driven Data Mining. ACM SIGKDD Explorations, Volume 9, Issue 2. December 2007. [Electronic Edition] [BibTeX]

6. Yanchang Zhao and Shichao Zhang, "Generalized Dimension-Reduction Framework for Recent-Biased Time Series Analysis," IEEE Transactions on Knowledge and Data Engineering, vol. 18, no. 2, February 2006, pp. 231-244. [Electronic Edition] [PDF] [BibTeX]

   Conference Papers:

1. Zhigang Zheng, Yanchang Zhao, Ziye Zuo and Longbing Cao. Negative-GSP: An Efficient Method for Mining Negative Sequential Patterns. To appear in Proc. of the 8th Australasian Data Mining Conference (AusDM 09), Melbourne, Australia, December 1-4, 2009.

2. Shanshan Wu, Yanchang Zhao, Huaifeng Zhang, Chengqi Zhang, Longbing Cao and Hans Bohlscheid. Debt Detection in Social Security by Adaptive Sequence Classification. To appear in Proc. of the 3rd International Conference on Knowledge Science, Engineering and Management (KSEM 09), Vienna, Austria, November 25-27, 2009.

3. Yanchang Zhao, Huaifeng Zhang, Shanshan Wu, Jian Pei, Longbing Cao, Chengqi Zhang and Hans Bohlscheid. Debt Detection in Social Security by Sequence Classification Using Both Positive and Negative Patterns. In Proc. of the 2009 European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD 09), Bled, Slovenia, September 7-11, 2009, pp. 648-663. [BibTeX]

4. Yanchang Zhao, Huaifeng Zhang, Longbing Cao, Chengqi Zhang and Hans Bohlscheid. Mining Both Positive and Negative Impact-Oriented Sequential Rules From Transactional Data. In Proc. of the 13th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 09), Bangkok, Thailand, April 27-30, 2009, pp.656-663. [Electronic Edition] [BibTeX]

5. Yanchang Zhao, Huaifeng Zhang, Longbing Cao, Chengqi Zhang and Hans Bohlscheid. Efficient Mining of Event-Oriented Negative Sequential Rules. In Proc. of the 2008 IEEE/WIC/ACM International Conference on Web Intelligence (WI 08), Sydney, Australia, December 9-12, 2008, pp. 336-342. [Electronic Edition] [BibTeX]

6. Chao Luo, Yanchang Zhao, Longbing Cao, Yuming Ou and Chengqi Zhang. Exception Mining on Multiple Time Series in Stock Market. In Proc. of the 2008 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology (WI-IAT 08) Workshops, Sydney, Australia, December 9-12, 2008, pp. 690-693. [Electronic Edition] [BibTeX]

7. Chao Luo, Yanchang Zhao, Longbing Cao, Yuming Ou and Li Liu. Outlier Mining on Multiple Time Series Data in Stock Market. In Proc. of the 10th Pacific Rim International Conference on Artificial Intelligence (PRICAI 08), Hanoi, Vietnam, December 15-19, 2008, pp. 1010-1015. [Electronic Edition] [BibTeX]

8. Yanchang Zhao, Huaifeng Zhang, Longbing Cao, Chengqi Zhang and Hans Bohlscheid. Combined Pattern Mining: from Learned Rules to Actionable Knowledge. In Proc. of the 21st Australasian Joint Conference on Artificial Intelligence (AI 08), Auckland, New Zealand, December 1-5, 2008, pp. 393-403. [Electronic Edition] [BibTeX]

9. Huaifeng Zhang, Yanchang Zhao, Longbing Cao and Chengqi Zhang, Combined Association Rule Mining. In Proc. of the Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 08), Osaka, Japan, May 20-23, 2008, pp. 1069-1074. [Electronic Edition] [BibTeX]

10. Huaifeng Zhang, Yanchang Zhao, Longbing Cao and Chengqi Zhang, "Class Association Rule Mining with Multiple Imbalanced Attributes," In Proc. of Twentieth Australian Joint Conference on Artificial Intelligence (AI 07), Gold Coast, Queensland, Australia, December 2-6, 2007, pp. 827-831. [Electronic Edition] [BibTeX]

11. Yanchang Zhao, Huaifeng Zhang, Fernando Figueiredo, Longbing Cao and Chengqi Zhang, "Mining for Combined Association Rules on Multiple Datasets," In Proc. of 2007 ACM SIGKDD Workshop on Domain Driven Data Mining (DDDM 07), San Jose, California, USA, August 12, 2007, pp. 18-23. [Electronic Edition] [PDF]

12. Longbing Cao, Yanchang Zhao, Fernando Figueiredo, Yuming Ou and Dan Luo, "Mining High Impact Exceptional Behavior Patterns", In Proc.of  PAKDD'07 Industrial Track, Nanjing, China, May 22-25, 2007, pp. 56-63. [Electronic Edition] [BibTeX]

13. Yanchang Zhao, Chengqi Zhang and Shichao Zhang, "Enhancing DWT for Recent-Biased Dimension Reduction of Time Series Data," In Proc. of the 19th Australian Joint Conference on Artificial Intelligence (AI 06), Hobart, Australia, December 4-8, 2006, pp. 1048-1053. [Electronic Edition] [PDF] [BibTeX]

14. Yanchang Zhao, Longbing Cao, Yvonne Morrow, Yuming Ou, Jiarui Ni and Chengqi Zhang, "Discovering Debtor Patterns of Centrelink Customers," In Proc. of The Australasian Data Mining Conference: AusDM 2006, Sydney, Australia, November 29-30, 2006, pp. 135-144.  [Electronic Edition] [PDF] [BibTeX]

15. Yanchang Zhao, Chengqi Zhang and Shichao Zhang, "Efficient Frequent Itemsets Mining by Sampling," In Proc. of the fourth International Conference on Active Media Technology (AMT 06), Brisbane, Australia, June 7-9 2006, pp.112-117. [PDF] [BibTeX]

16. Lianwei Zhao, Siwei Luo, Yanchang Zhao, Lingzhi Liao and Zhihai Wang, "Regularized Semi-supervised Classification on Manifold," In Proc. of the 10th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 06), Singapore, April 9-2, 2006, pp. 20-29. [BibTeX]

17. Yanchang Zhao, Chengqi Zhang, Shichao Zhang  and Lianwei Zhao, "Adapting K-Means Algorithm for Discovering Clusters in Subspaces", In Proc. of the 8th Asia-Pacific Web Conference (APWeb 06), Harbin, China, January 16-18, 2006, pp. 53-62. [Electronic Edition] [PDF] [BibTeX]

18. Lianwei Zhao, Yanchang Zhao, Siwei Luo and Chao Shao, "Construction Algorithm of Principal Curves in the Sense of Limit", In Proc. of the 18th Australian Joint Conference on Artificial Intelligence (AI 05), Sydney, Australia, December 5-9, 2005, pp. 264-273. [BibTeX]

19. Yanchang Zhao, Chengqi Zhang and Shichao Zhang, "A Recent-Biased Dimension Reduction Technique for Time Series Data", In Proc. of the 9th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 05), Hanoi, Vietnam, May 18-20, 2005, pp. 751-757. [Electronic Edition] [PDF] [BibTeX]

20. Yanchang Zhao, Chengqi Zhang and Shichao Zhang, "Discovering Interesting Association Rules by Clustering", In Proc. of the 17th Australian Joint Conference on Artificial Intelligence (AI 04), Cairns, Australia, December 6-10, 2004, pp. 1055-1061. [Electronic Edition] [PDF] [BibTeX]

21. Yanchang Zhao, Chengqi Zhang and Yi-Dong Shen, "Clustering High-Dimensional Data with Low-Order Neighbors", In Proc. of the 2004 IEEE/WIC/ACM International Conference on Web Intelligence (WI 04), Beijing, China, September 20-24, 2004, pp. 103-109. [Electronic Edition] [PDF] [BibTeX]

22. Yanchang Zhao and J. Song, “AGRID: An Efficient Algorithm for Clustering Large High-Dimensional Datasets,” In Proc. of the 7th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 03), Seoul, Korea, April 30- May 2, 2003, pp. 271-282. [Electronic Edition] [BibTeX]

Fellowship

Professional Activities

Professional Memberships

Conferences on Data Mining

* The above ranking is from CORE (the Computing Research and Education Association of Australasia).

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