Efficient Techniques for Mining Exceptional Patterns

Funding: 2006: $88,000
2007: $78,000
2008: $80,000

Project Member(s): Zhang, C., Cao, L.

Funding or Partner Organisation: Australian Research Council (ARC Discovery Projects)

Start year: 2006

Summary: Existing association rule mining is specifically designed to find strong patterns that have high predictive accuracy or correlation. Many useful patterns, for example, out-expectation patterns with low supports, are certainly pruned. This project aims at developing novel theories, techniques and methodologies for discovering two new kinds of exceptional patterns: class-bridge rules and out-expectation patterns. These patterns are essentially different from traditional association rules, but are much more useful than traditional ones to applications such as cross-sales, trend prediction, detecting behavior changes, and recognizing rare but significant events. This project will deliver a paradigm shift from existing data mining techniques.

Publications:

Wang, H, Zhang, P, Tsang, I, Chen, L & Zhang, C 1970, 'Defragging Subgraph Features for Graph Classification', Proceedings of the 24th ACM International on Conference on Information and Knowledge Management, CIKM'15: 24th ACM International Conference on Information and Knowledge Management, ACM, Melbourne, VIC, Australia, pp. 1687-1690.
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Longbing, C 2009, 'Introduction to Domain Driven Data Mining' in Cao, L, Yu, PS, Zhang, C & Zhang, H (eds), Data Mining for Business Applications, Springer US, New York, USA, pp. 3-10.
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Wu, S, Zhao, Y, Zhang, H, Zhang, C, Cao, L & Bohlscheid, H 2009, 'Debt Detection in Social Security by Adaptive Sequence Classification' in Karagiannis, D & Jin, Z (eds), Knowledge Science, Engineering and Management, Springer Berlin Heidelberg, Germany, pp. 192-203.
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Cao, L & He, T 2009, 'Developing actionable trading agents', Knowledge and Information Systems, vol. 18, no. 2, pp. 183-198.
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Cao, L & Yu, P 2009, 'Behavior Informatics: An Informatics Perspective for Behavior Studies', IEEE Computational Intelligence Bulletin, vol. 10, no. 1, pp. 6-11.

Qin, Y, Zhang, S, Zhu, X, Zhang, J & Zhang, C 2009, 'POP algorithm: Kernel-based imputation to treat missing values in knowledge discovery from databases', Expert Systems with Applications, vol. 36, no. 2, pp. 2794-2804.
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Yan, X, Zhang, C & Zhang, S 2009, 'Genetic algorithm-based strategy for identifying association rules without specifying actual minimum support', Expert Systems with Applications, vol. 36, no. 2, pp. 3066-3076.
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Zhang, S, Chen, F, Jin, Z & Wang, R 2009, 'Mining class-bridge rules based on rough sets', Expert Systems with Applications, vol. 36, no. 3, pp. 6453-6460.
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Zhang, S, Wang, R & Jin, Z 2009, 'Strategies for complex data cube queries', Applied Intelligence, vol. 31, no. 3, pp. 332-346.
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Zhao, G, Xiong, Y, Cao, L, Luo, D, Su, X & Zhu, Y 1970, 'A Cost-Effective LSH Filter for Fast Pairwise Mining', 2009 Ninth IEEE International Conference on Data Mining, 2009 Ninth IEEE International Conference on Data Mining (ICDM), IEEE, Miami, Florida, USA, pp. 1088-1093.
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Zheng, Z, Zhao, Y, Zuo, Z & Cao, L 1970, 'Negative-GSP: An efficient method for mining negative sequential patterns', Conferences in Research and Practice in Information Technology Series, Australian Data Mining Conference, Australian Computer Society, Melbourne, Australia, pp. 63-67.

Chen, Q, Zhang, C & Zhang, S 2008, Secure Transaction Protocol Analysis, 1, Springer Berlin Heidelberg, Berlin, Germany.
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Cao, L, Zhao, Y & Zhang, C 2008, 'Mining Impact-Targeted Activity Patterns in Imbalanced Data', IEEE Transactions on Knowledge and Data Engineering, vol. 20, no. 8, pp. 1053-1066.
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CAO, L, ZHAO, Y, ZHANG, C & ZHANG, H 2008, 'ACTIVITY MINING: FROM ACTIVITIES TO ACTIONS', International Journal of Information Technology & Decision Making, vol. 07, no. 02, pp. 259-273.
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Qin, Y & Zhang, S 2008, 'Empirical likelihood confidence intervals for differences between two datasets with missing data', Pattern Recognition Letters, vol. 29, no. 6, pp. 803-812.
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Zhang, S, Huang, Z, Zhang, J & Zhu, X 2008, 'Mining follow-up correlation patterns from time-related databases', Knowledge and Information Systems, vol. 14, no. 1, pp. 81-100.
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Zhang, S, Wu, X, Zhang, C & Lu, J 2008, 'Computing the minimum-support for mining frequent patterns', Knowledge and Information Systems, vol. 15, no. 2, pp. 233-257.
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Zhang, S, Zhang, J, Zhu, X, Qin, Y & Zhang, C 2008, 'Missing Value Imputation Based on Data Clustering', Lecture Notes in Computer Science, vol. 4750, no. 2008, pp. 128-138.
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Cao, L, Luo, D, Xiao, Y & Zheng, Z 1970, 'Agent Collaboration for Multiple Trading Strategy Integration.', KES-AMSTA, International KES Symposium on Agents and Multiagent systems - Technologies and Applications, Springer, Incheon, Korea,, pp. 361-370.
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Luo, C, Zhao, Y, Cao, L, Ou, Y & Zhang, C 1970, 'Exception Mining on Multiple Time Series in Stock Market', 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology, 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology, IEEE, Sydney, Australia, pp. 690-693.
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Zhao, Y, Zhang, H, Cao, L, Zhang, C & Bohlscheid, H 1970, 'Combined Pattern Mining: From Learned Rules to Actionable Knowledge', Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Australasian Joint Conference on Artificial Intelligence, Springer Berlin Heidelberg, Auckland, Newzealand, pp. 393-403.
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Cao, L, Luo, D & Zhang, C 2007, 'Knowledge actionability: satisfying technical and business interestingness', International Journal of Business Intelligence and Data Mining, vol. 2, no. 4, pp. 496-496.
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Qin, Y, Zhang, S, Zhu, X, Zhang, J & Zhang, C 2007, 'Semi-parametric optimization for missing data imputation', Applied Intelligence, vol. 27, no. 1, pp. 79-88.
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Yan, X, Zhang, S & Zhang, C 2007, 'ON DATA STRUCTURES FOR ASSOCIATION RULE DISCOVERY', Applied Artificial Intelligence, vol. 21, no. 2, pp. 57-79.
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Zhang, S, Zhang, J & Zhang, C 2007, 'EDUA: An efficient algorithm for dynamic database mining', Information Sciences, vol. 177, no. 13, pp. 2756-2767.
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Cao, L 1970, 'Multi-strategy Integration for Actionable Trading Agents', 2007 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology - Workshops, 2007 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology - Workshops, IEEE, San Jose, USA, pp. 487-490.
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Cao, L, Zhao, Y, Figueiredo, F, Ou, Y & Luo, D 1970, 'Mining High Impact Exceptional Behavior Patterns', Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Pacific-Asia Conference on Knowledge Discovery and Data Mining, Springer Berlin Heidelberg, Nanjing, China, pp. 56-63.
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Luo, D, Cao, L, Ni, J & Liu, L 1970, 'Building Agent Service Oriented Multi-Agent Systems', Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), International KES Symposium on Agents and Multiagent systems - Technologies and Applications, Springer Berlin Heidelberg, Wroclaw, Poland, pp. 11-20.
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Ou, Y, Cao, L, Yu, T & Zhang, C 1970, 'Detecting Turning Points of Trading Price and Return Volatility for Market Surveillance Agents', 2007 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology - Workshops, 2007 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology - Workshops, IEEE, Fremont, CA, pp. 491-+.
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Zhang, S, Wang, R & Guo, Y 1970, 'Knowledge Science, Engineering and Management', Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), International Conference on Knowledge Science, Engineering and Management, Springer Berlin Heidelberg, Guilin, China, pp. 612-624.
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Keywords: Data Mining, Knowledge Discovery in Database, Exceptional Patterns,

FOR Codes: Database Management, Pattern Recognition, Application tools and system utilities, Information processing services, Application packages, Information Storage, Retrieval and Management, Records and Information Management (excl. Business Records and Information Management), Information Processing Services (incl. Data Entry and Capture), Pattern Recognition and Data Mining, Recordkeeping informatics, Database systems, Information systems, technologies and services not elsewhere classified

Acknowledgement of Country

UTS acknowledges the Gadigal people of the Eora Nation, the Boorooberongal people of the Dharug Nation, the Bidiagal people and the Gamaygal people, upon whose ancestral lands our university stands. We would also like to pay respect to the Elders both past and present, acknowledging them as the traditional custodians of knowledge for these lands.