Publications

Below is an incomplete list of my publications on data mining and machine learning. A partial list is also available at DBLP: Yanchang Zhao. 

See my profile on Google Scholar to find out citations to my publications.

Monographs:

1. Yanchang Zhao. "R and Data Mining: Examples and Case Studies", ISBN 978-0-12-396963-7, December 2012. Academic Press, Elsevier. 256 pages.

2. Longbing Cao, Philip S. Yu, Chengqi Zhang and Yanchang Zhao. "Domain Driven Data Mining", ISBN 978-1-4419-5737-5. Springer. 2010. 248 pages.

Edited Books:

1. Yanchang Zhao and Yonghua Cen (Eds.). "Data Mining Applications with R", ISBN 978-0-12-411511-8, December 2013. Academic Press, Elsevier. 514 pages.

2. 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. 372 pages. [Book details at the publisher website]

Book Chapters:

1. Chao Luo, Yanchang Zhao, et al. "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, et al. "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. [PDF]

5. Yanchang Zhao, et al. "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]
   
   

Conference/Workshop Proceedings:

1. Laurence A. F. Park, Heitor Murilo Gomes, Maryam Doborjeh, Yee Ling Boo, Yun Sing Koh, Yanchang Zhao, Graham Williams, Simeon Simoff (Eds.). Data Mining - Proceedings of the 20th Australasian Conference on Data Mining (AusDM 2022), Western Sydney, Australia, 12-15 December 2022. Communications in Computer and Information Science, Springer 2022, ISBN 978-981-19-8745-8. https://doi.org/10.1007/978-981-19-8746-5 

2. Y. Xu, X. R. Wang, A. Lord, Y. L. Boo, R. Nayak, Y. Zhao, G. Williams (Eds.). Data Mining - Proceedings of the 19th Australasian Conference on Data Mining  (AusDM 2021), Brisbane, QLD, Australia, December 14-15, 2021. Communications in Computer and Information Science 1504, Springer 2021, ISBN 978-981-16-8530-9.

3. Thuc D. Le, Kok-Leong Ong, Yanchang Zhao, Warren H. Jin, Sebastien Wong, Lin Liu, Graham Williams: Proceedings of the 17th Australasian Data Mining (AusDM 2019) Conference, Adelaide, SA, Australia, December 2-5, 2019. Communications in Computer and Information Science 1127, Springer 2019, ISBN 978-981-15-1698-6. DOI: https://doi.org/10.1007/978-981-15-1699-3

4. Md. Rafiqul Islam, Yun Sing Koh, Yanchang Zhao, Warwick Graco, David Stirling, Chang-Tsun Li, Zahidul Islam: Data Mining - 16th Australasian Conference, AusDM 2018, Bathurst  NSW, Australia, November 28-30, 2018, Revised Selected Papers. Communications in Computer and Information Science 996, Springer 2019, ISBN 978-981-13-6660-4

5. Yanchang Zhao, Md Zahidul Islam, Glenn Stone, Kok-Leong Ong, Dharmendra Sharma and Graham Williams (Eds.). Data Mining and Analytics 2016 - Proceedings of the 14th Australasian Data Mining Conference (AusDM 2016), Canberra, Australia, 6-8 December 2016. CRPIT Vol. 170. Australian Computer Society. ISBN 978-1-921770-50-0. [Electronic Edition]

6. Kok-Leong Ong, Yanchang Zhao, Md Glenn Stone, Md Zahidul Islam: Thirteenth Australasian Data Mining Conference, AusDM 2015, Sydney, Australia, August 2015. CRPIT 168, Australian Computer Society 2015, ISBN 978-1-921770-18-0

7. Xue Li, Lin Liu, Kok-Leong Ong, Yanchang Zhao: Twelfth Australasian Data Mining Conference, AusDM 2014, Brisbane, Australia, November 2014. CRPIT 158, Australian Computer Society 2014, ISBN 978-1-921770-17-3

8. Peter Christen, Paul Kennedy, Lin Liu, Kok-Leong Ong, Andrew Stranieri and Yanchang Zhao (Eds.). Data Mining and Analytics 2013 -  Proceedings of the Eleventh Australasian Data Mining Conference (AusDM'13), Sydney, Australia, 13-15 November 2013. CRPIT Vol. 146. Australian Computer Society.

9. Yanchang Zhao, Jiuyong Li, Paul J. Kennedy, Peter Christen: Tenth Australasian Data Mining Conference, AusDM 2012, Sydney, Australia, December 5-7, 2012. CRPIT 134, Australian Computer Society 2012, ISBN 978-1-921770-14-2

10. Philip S. Yu, Yanchang Zhao, Graham Williams, Carlos Soares. Workshop on Domain Driven Data Mining (DDDM 2008), In Proc. of ICDM Workshops 2008. ISBN 978-0-7695-3503-6. IEEE Computer Society, 2008. [Electronic Edition]

11. P. S. Yu, C. Zhang, G. Williams, L. Cao, Y. Zhao (Eds.). Proc. of the ACM SIGKDD Workshop on Domain Driven Data Mining, ISBN 978-1-59593-846-6, ACM Press, 2007. [Electronic Edition]
    
    

Journal Articles:

1. Ainura Tursunalieva, David L. J. Alexander, Rob Dunne, Jiaming Li, Luis Riera and Yanchang Zhao. Making Sense of Machine Learning: A Review of Interpretation Techniques and Their Applications. Applied Sciences, 14(2), 496, January 2024; DOI: https://doi.org/10.3390/app14020496.

2. Ha Tran, Thuc Le, Jiuyong Li, Lin Liu, Jixue Liu, Yanchang Zhao and Tony Waters. Personalized Interventions to Increase the Employment Success of People with Disability. IEEE Transactions on Big Data, vol. 9, no. 6, December 2023, pp. 1561-1574. DOI: https://doi.org/10.1109/TBDATA.2023.3291547

3. Md Asif-Ur-Rahman, Bayzid Ashik Hossain, Michael Bewong, Md Zahidul Islam, Yanchang Zhao, Jeremy Groves, Rory Judith. A semi-automated hybrid schema matching framework for vegetation data integration. Expert Systems with Applications, Volume 229, Part A, November 2023, ISSN 0957-4174, https://doi.org/10.1016/j.eswa.2023.120405.

4. Yanchang Zhao, Bin Liang, et al. Energy Saving Optimisation for Water Distribution Networks - Applying Intelligent Network Optimisation Models. The Water e-Journal, vol. 4, no. 4, December 2019. [Electronic Edition]

5. Yanchang Zhao, et al. "Enhancing Grid-Density based Clustering for High Dimensional Data." Journal of Systems and Software, 84(9), 2011, pp. 1524-1539.

6. Longbing Cao, Yanchang Zhao, et al. "Flexible Frameworks for Actionable Knowledge Discovery." IEEE Transactions on Knowledge and Data Engineering, vol. 22, issue 9, 2010, pp. 1299-1312.

7. Huaifeng Zhang, Yanchang Zhao, et al. "Customer Activity Sequence Classification for Debt Prevention in Social Security." Journal of Computer Science and Technology, vol. 24, no. 6, November 2009.

8. 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]

9. Longbing Cao, Yanchang Zhao, et al. "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]

10. 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]

11. 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] [BibTeX]

   Conference Papers:

1. Haohui Chen, Claire Mason, Yanchang Zhao, Qinyong Wang. DBSSM: Deep BERT-based Semantic Skill Matching from Resumes to a Public Skill Taxonomy.  To appear in Proc. of the 37th Australasian Joint Conference on Artificial Intelligence (AJCAI 2024), Melbourne, Australia, 25-29 Nov 2024.

2. Wentao Gao, Ziqi Xu, Jiuyong Li, Lin Liu, Jixue Liu, Thuc Duy Le, Debo Cheng, Yanchang Zhao, Yun Chen. TSI: A multi-view representation learning approach for time series forecasting. To appear in Proc. of the 37th Australasian Joint Conference on Artificial Intelligence (AJCAI 2024), Melbourne, Australia, 25-29 Nov 2024.

3. Richard Reynaldo Wironoto Susilo, Yanchang Zhao, Reena Kapoor, Devesh Bhogal, Peter Toscas, Klaus Joehnk. Effective River Water Temperature Forecasting with Transformer. To appear in Proc. of the 22nd Australasian Data Science and Machine Learning Conference (AusDM 2024), Melbourne, Australia, 25-27 Nov 2024.

4. Devesh Bhogal, Yanchang Zhao, Reena Kapoor and Peter Toscas. A Comparative Study of Water Temperature Forecasting Methods. In Proc. of the 2023 IEEE International Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT), Venice, Italy, 26-29 October 2023.

5. Hui Luo, Zhifeng Bao, J. Shane Culpepper, Mingzhao Li and Yanchang Zhao. Facility Relocation Search For Good: When Facility Exposure Meets User Convenience. In Proc. of the ACM Web Conference 2023, Austin, Texas, USA, 30 Apr to 4 May 2023.

6. Ha Tran, Thuc Le, Jiuyong Li, Lin Liu, Jixue Liu, Yanchang Zhao and Tony Waters. Decision Support for Disability Employment using Counterfactual Survival Analysis. In Proc. of the 2022 IEEE International Conference on Big Data, Osaka, Japan, 17-20 December 2022.  Award of the best application paper.

7. Ray Lindsay and Yanchang Zhao. A Study of the Effectiveness of Correction Factors for Log Transforms in Ensemble Models. In Proc. of the 18th International Conference on Advanced Data Mining and Applications (ADMA 2022), Brisbane, Australia, 28-30 Nov 2022.

8. Ha Tran, Thuc Le, Jiuyong Li, Lin Liu, Jixue Liu, Yanchang Zhao and Tony Waters. What is the Most Effective Intervention to Increase Job Retention for this Disabled Worker? In Proc. of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2022). Washington DC, USA, 14-18 Aug 2022. 

9. Ha Tran, Thuc Le, Jiuyong Li, Lin Liu, Jixue Liu, Yanchang Zhao and Tony Waters. Recommending Personalized Interventions to Increase Employability of Disabled Jobseekers. In Proc. of the 26th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2022), Chengdu, China, 16-19 May 2022.

10. Yanchang Zhao, Haohui Chen, and Claire Mason. A Framework of Duplicate Detection from Online Job Postings. In Proc. of the 20th IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT 2021), Melbourne, Australia, 14-17 Dec 2021.

11. Darren Yates, Md Zahidul Islam, Yanchang Zhao, Richi Nayak, Vladimir Estivill-Castro and Salil Kanhere. PostMatch: a Framework for Efficient Address Matching. In Proc. of the 19th Australasian Data Mining Conference (AusDM 2021), Brisbane, Australia, 13-15 Dec 2021.

12. Ha Tran, Thuc Le, Jiuyong Li, Lin Liu, Jixue Liu, Yanchang Zhao, and Tony Waters. Recommending the Most Effective Interventions to Improve Employment for Australians with Disability. In Proc. of the ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2021); Singapore. ACM; 2021.

13. Ha Tran, Thuc Le, Jiuyong Li, Lin Liu, Jixue Liu, Yanchang Zhao, and Tony Waters. Intervention Recommendation for Improving Disability Employment. In Proc. of the IEEE International Conference on Big Data 2020. 10-13 Dec 2020, pp. 1671-1680. Award of the best application paper.

14. Qinyong Wang, Hongzhi Yin, Tong Chen, Zi Huang, Hao Wang, Yanchang Zhao, and Nguyen Quoc Viet Hung. 2020. Next Point-of-Interest Recommendation on Resource-Constrained Mobile Devices. In Proceedings of The Web Conference 2020 (WWW '20). Association for Computing Machinery, New York, NY, USA, 906–916.

15. Yanchang Zhao, Bin Liang, et al. Optimising Pump Scheduling for Water Distribution Networks. In Proc. of the 32nd Australasian Joint Conference on Artificial Intelligence (AI 2019), Adelaide, Australia, 2-5 December 2019.

16. Marcus Suresh, Ronnie Taib, Yanchang Zhao and Warren Jin. Sharpening the BLADE: Missing Data Imputation using Supervised Machine Learning. In Proc. of the 32nd Australasian Joint Conference on Artificial Intelligence (AI 2019), Adelaide, Australia, 2-5 December 2019.

17. Martin Nolan, Danial Stratford, Nicky Grigg, Yanchang Zhao, Sam Nicol and Carmel Pollino, Assessing change in regional communities as a consequence of water recovery: Issues of scale and zoning when combining data. The 23rd International Congress on Modelling and Simulation, Canberra, Australia, 1-6 December 2019.

18. Yanchang Zhao, Bin Liang, et al. An Application of Energy Saving Optimisation to Water Distribution Networks. OZWater 2019, Melbourne, Australia, 7-9 May 2019.

19. Yanchang Zhao. Analysing Twitter Data with Text Mining and Social Network Analysis. In Proc. of the 11th Australasian Data Mining & Analytics Conference (AusDM 2013), Canberra, Australia, November 13–15, 2013.

20. Chao Luo, Yanchang Zhao, et al. Agent-based Subspace Clustering. In Proc. of the 15th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 11) - Part II, Shenzhen, China, 24-27 May 2011, pp. 370-381.

21. Yanchang Zhao, Hans Bohlscheid, Shanshan Wu and Longbing Cao. Less Effort, More Outcomes: Optimising Debt Recovery with Decision Trees. In Proc. of ICDM'10 Workshop on Applications of Data Mining and Modeling in Government and Industry, Sydney, Australia, 14 December 2010, pp. 655-660.

22. Zhigang Zheng, Yanchang Zhao, et al. An Efficient GA-Based Algorithm for Mining Negative Sequential Patterns. In Proc. of the 14th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 10), Hyderabad, India, 21-24 June 2010, pp. 262-273.

23. Zhigang Zheng, Yanchang Zhao, et al. Negative-GSP: An Efficient Method for Mining Negative Sequential Patterns. In Proc. of the 8th Australasian Data Mining Conference (AusDM 09), Melbourne, Australia, December 1-4, 2009.

24. Shanshan Wu, Yanchang Zhao, . Debt Detection in Social Security by Adaptive Sequence Classification. In Proc. of the 3rd International Conference on Knowledge Science, Engineering and Management (KSEM 09), Vienna, Austria, November 25-27, 2009, pp.192-203.[BibTeX]

25. Yanchang Zhao, et al. 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]

26. Yanchang Zhao, et al. 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]

27. Yanchang Zhao, et al. 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]

28. Chao Luo, Yanchang Zhao, et al. 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]

29. Chao Luo, Yanchang Zhao, et al. 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]

30. Yanchang Zhao, et al. 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]

31. 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]

32. 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]

33. Yanchang Zhao, et al, "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]

34. Longbing Cao, Yanchang Zhao, et al. "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]

35. 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] [BibTeX]

36. Yanchang Zhao, et al. "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] [BibTeX]

37. 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. [BibTeX]

38. Lianwei Zhao, Siwei Luo, Yanchang Zhao, et al. "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]

39. 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] [BibTeX]

40. Lianwei Zhao, Yanchang Zhao, et al. "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]

41. 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] [BibTeX]

42. 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] [BibTeX]

43. 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] [BibTeX]

44. Yanchang Zhao, “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]