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J. Li, S. Ma, T. Le, L. Liu, and J. Liu, Causal Decision Trees , IEEE Transactions on Knowledge and Data Engineering, 29(2), 257-271, 2017.
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J. Li, T. Le, J. Liu, J. Liu, J. Zhou, B. Sun, and S. Ma, From Observational Studies to Causal Rule Mining , ACM Transactions on Intelligent Systems and Technology, 7(2), 14:1-17, 2016.
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J. Li, L. Liu, T. Le, Practical approaches to causal relationship exploration , SpringerBriefs in Electrical and Computer Engineering , Springer 2015.
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J. Li, J. Liu, H. Toivonen, K. Satou, Y. Sun, and B. Sun, Discovering statistically non-redundant subgroups, Knowledge-Based Systems, 67, 315-327, 2014. (Program is available in my software section.)
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J. Li, J. Liu, H. Toivonen, and J. Yong, Effective pruning for the discovery of conditional functional dependencies, The Computer Journal, 56(3), 378-392, 2013.
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J. Li, From association analysis to causal discovery, Machine Learning and Sensory Data Analysis, 1-2, 2013.
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J. Li, T. Le, L. Liu, J. Liu, Z. Zhou, and B. Sun, Mining causal association rules, Proceedings of ICDM Workshop on Causal Discovery (CD), 114-123, 2013, IEEE CS Press.
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Z. Jin, J. Li, L. Liu, T. Le, B. Sun, and R. Wang, Discovery of causal rules using partial association, Proceedings of IEEE International Conference on Data Mining (ICDM), 309-318, 2012, IEEE CS Press.
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J. Liu, J. Li, C. Liu and Y. Chen, Discover dependencies from data - a review, IEEE Transactions on Knowledge and Data Engineering (TKDE), 24(2), 251-264, 2012.
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J. Li, A. Fu, and P. Fahey, Efficient discovery of risk patterns in medical data, Artificial Intelligence in Medicine, 45, 77-89, 2009.
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J. Li, On optimal rule discovery, IEEE Transactions on Knowledge and Data Engineering, 18 (4), 2006, 460-471.
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J. Li, A. Fu, H. He, J. Chen, H. Jin, D. McAullay, G. Williams, R. Sparks, C. Kelman, Mining risk patterns in medical data, In Proceedings of ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 770 – 775, 2005, ACM Press.
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J. Li, H. Shen and R. Topor, Mining the informative rule set for prediction, Journal of Intelligent Information Systems, 22:2, 155-174, 2004.
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J. Li and Y. Zhang, Direct interesting rule generation, In Proceedings of IEEE International Conference on Data Mining (ICDM), 155 - 162, 2003.
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J. Li, H. Shen and R. Topor, Mining the optimal class association rule set, Knowledge-based Systems, 15(7), 399 -405, 2002.
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J. Li, H. Shen and R. Topor, Mining the smallest association rule set for predictions, In Proceedings of IEEE international conference on data mining (ICDM), 361 - 368, 2001.
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J. Li, H. Shen and R. Topor, An adaptive method of numerical attribute merging for quantitative association rule mining, In Proceedings of the 5th international computer science conference (ICSC), 41 - 50, LNCS 1749, 1999, Springer.
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Y. Sun, J. Li, J. Liu, C. Chow, B. Sun, and R. Wang, Using causal discovery for feature selection in multivariate numerical time series, Machine Learning, in press, 2014.
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Y. Sun, J. Li, J. Liu, B. Sun and C. Chow, An improvement of symbolic aggregate approximation distance measure for time series, Neurocomputing, 138, 189-198, 2014.
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J. Li, Robust rule based predictions, IEEE Transactions on Knowledge and Data Engineering, 18(8), 2006, 1043-1054.
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J. Li, J. Jones, Using multiple and negative target rules to make classifier more understandable, Knowledge-based Systems, 19(6), 2006.
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F. Khalil, J. Li, and H. Wang, An integrated model for next page access prediction, International Journal of Knowledge and Web Intelligence, 1(1/2), 48 – 80, 2009.
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H. Hu and J. Li, Using association rules to make rule-based classifiers robust, In Proceedings of Sixteenth Australasian Database Conference (ADC), 47-52, 2005, ACS Press.
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J. Li, R. Topor and H. Shen, Construct robust rule sets for classification, In Proceedings of the Eighth ACMKDD International Conference on Knowledge Discovery and Data Mining (KDD), 564 -569, 2002, ACM Press.
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H. Hu, J. Li, H. Wang, G. Daggard and M. Shi, A maximally diversified multiple decision tree algorithm for microarray data classification, In Proceedings first Workshop on Intelligent Systems for Bioinformatics, 2006.
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H. Hu, J. Li, A. Plank, H. Wang, and G. Daggard, A comparative study of classification methods for microarray data analysis , In Proceedings of Australian Data Mining conference, 31 - 35, 2006, ACS Press.
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J. Li, J. Liu, L. Liu, T. Le, S. Ma, and Y. Han, Discrimination detection by causal effect estimation, IEEE International Conference on Big Data, 2017..
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S. Sattar, J. Li, J. Liu, R. Heatherly and B. Malin A probabilistic approach to mitigate composition attacks on privacy in non-coordinated environments, Knowledge-based Systems, 67, 361-372, 2014.
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S. Sattar, J. Li, X. Ding, J. Liu, and M. Vincent A general framework for privacy preserving data publishing, Knowledge-based Systems, 54, 276-287, 2013.
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X. Ding, Q. Yu, J. Li, J. Liu, and H. Jin Distributed Anonymization for Multiple Data Providers in a Cloud System, International Conference on Database Systems for Advanced Applications (DASFAA), 346-360, 2013.
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X. Sun, H. Wang, J. Li and Y. Zhang, Satisfying privacy requirements before data anonymization, The Computer Journal, 55(4), 422-437, 2012.
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M. M. Baig, J. Li, J. Liu, X. Ding, and H. Wang, Data privacy against composition attack, International Conference on Database Systems for Advanced Applications (DASFAA), 320-334, 2012.
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J. Li, J. Liu, M. Baig and R. Wong, Information based data anonymization for classification utility, Data and Knowledge Engineering, 70(12), 1030-1045, 2011 (implementation).
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X. Sun, H. Wang, J. Li and J. Pei, Publishing anonymous survey rating data, Data Mining and Knowledge Discovery, 23(3), 379-406, 2011.
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M. Baig, J. Li, J. Liu and H. Wang, Cloning for privacy protection in multiple independent data publications, In Proceedings of ACM Conference on Information and Knowledge Management (CIKM), 2011
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R. Wong, J. Li, A. Fu, and K. Wang, (alpha, k)-anonymous data publishing, Journal of Intelligent Information Systems, 33(2) 209-234, 2009.
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X Sun, H Wang, J. Li, T. M. Truta, Enhanced p-sensitive k-anonymity models for privacy preserving data publishing, Transactions on Data Privacy, 1(2): 53-66 2008
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J. Li, R. Wong, A. Fu, J. Pei, Anonymisation by local recoding in data with hierarchical taxonomies, IEEE Transactions on Knowledge and Data Engineering, 20(8), 2008. 1181-1194.
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J. Li, H Wang, Huidong Jin, and Jianming Yong, Current developments of k-Anonymous data releasing, Electronic Journal of Health Informatics, 3(1), 2008.
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R. Wong, J. Li, A. Fu, K. Wang, (alpha, k)-anonymity: an enhanced k-anonymity model for privacy-preserving data publishing, In Proceedings of the twelfth ACM SIGKDD international conference on knowledge discovery and data mining (KDD), 754-759, 2006.
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J. Li, R. Wong, A.Fu, J. Pei, Achieving k-Anonymity by clustering in attribute hierarchical structures, In Proceedings of 8th International Conference on Data Warehousing and Knowledge Discovery, 405-416, 2006, Springer.
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T. Le, L. Liu, J. Zhang, B. Liu, and J. Li, From miRNA regulation to miRNA - TF co-regulation: computational approaches and challenges , Briefings in Bioinformatics, In press, 2014.
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J. Zhang, T. Le, L. Liu, B. Liu, J. He, G. J. Goodall, and J. Li, Identifying direct miRNA–mRNA causal regulatory relationships in heterogeneous data, Journal of Biomedical Informatics, In press, 2014.
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J. Zhang, T. Le, L. Liu, B. Liu, J. He, G. J. Goodall, and J. Li, Inferring condition-specific miRNA activity from matched miRNA and mRNA expression data, Bioinformatics, 30(21), 3070-3077, 2014. (Supplementary files)
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T. Le, L. Liu, A. Tsykin, G. J. Goodall, B. Liu, B. Sun, and J. Li, Inferring microRNA-mRNA causal regulatory relationships from expression data, Bioinformatics, 29(6), 765-771, 2013. (Supplementary files)
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T. Le, L. Liu, B. Liu, A. Tsykin, G. J. Goodall, Kenji Satou, and J. Li, Inferring microRNA and transcription factor regulatory networks in heterogeneous data, BMC Bioinformatics, 14, 92, 2013.
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B. Li, J. Li, and M. Carins, Identifying miRNAs, targets and functions, Briefings in Bioinformatics, 15(1), 1-19, 2014.
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B. Liu, L. Liu, A. Tsykin, G. Goodall, J. Green, M. Zhu, C. Kim and J. Li, Identifying functional miRNA-mRNA regulatory modules with correspondence latent Dirichlet allocation, Bioinformatics, 26(24), 3105-3111, 2010.
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B. Liu, J. Li, A, Tsykin, L. Liu, A. B. Gaur and G. J. Goodall, Exploring complex miRNA-mRNA interactions with Bayesian networks by splitting-averaging strategy, BMC Bioinformatics, 2009 (10), 408.
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B Liu, J Li, A Tsykin, Discovery of functional miRNA-mRNA regulatory modules with computational methods, Journal of Biomedical Informatics, 42(4), 685-691, 2009.
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J. Li, A. Fu, and P. Fahey, Efficient discovery of risk patterns in medical data, Artificial Intelligence in Medicine, 45, 77-89, 2009.
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J. Li, A. Fu, H. He, J. Chen, H. Jin, D. McAullay, G. Williams, R. Sparks, C. Kelman,Mining risk patterns in medical data, In Proceedings of ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 770 – 775, 2005, ACM Press.
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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 KES, 1225-1231, 2005.
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H. He, H. Jin, J. Chen, D. McAullay, J. Li, T. Fallon, Analysis of breast feeding data using data mining methods, In Proceedings of Australian data mining conference (AusDM), 43 -48, 2006, ACS press.
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F. Khalil, J. Li, and H Wang, Integrating recommendation models for improved Web page prediction accuracy, In Proceedings of the Thirty-First Australasian Computer Science Conference, Wollongong, 2008.
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F. Khalil, J. Li and, H. Wang, Integrating markov model with clustering for predicting Web page accesses, In Proceedings of Australian World Wide Conference, 2007.
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F. Khalil, J. Li, H. Wang, A framework of combining Markov model with association rules for predicting Web page accesses, In Proceedings of Australian Data Mining Conference, 166 -173, 2006, ACS Press
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H. Hu, J. Li, H. Wang, G. Daggard and M. Shi, A maximally diversified multiple decision tree algorithm for microarray data classification, In Proceedings of the first Workshop on Intelligent Systems for Bioinformatics.2006.
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H. Hu, J. Li, H. Wang, and G. Daggard, Combined gene selection methods for microarray data analysis, In Proceedings of 10th International Conference Knowledge-Based Intelligent Information and Engineering Systems, (KES), 976--983, 2006, LNAI 4251, 2006, Springer.
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H. Hu, J. Li, A. Plank, H. Wang, and G. Daggard, A comparative study of classification methods for microarray data Analysis, In Proceedings of Australian Data Mining conference, 31-35, 2006, ACS Press.
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H. Li, J. Li, L. Liu, J. Liu, I. Lee, and J. Zhao, Exploring Groups from Heterogeneous Data via Sparse Learning, In Proceedings of Seventeenth Pacific-Asian Conference in Knowledge Discovery and Data Mining (PAKDD), 556-567, 2013.
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J. Li, X. Huang, C. Selke, J. Yong, A fast algorithm for finding correlation clusters in noise data, In Proceedings of Eleventh Pacific-Asian Conference in Knowledge Discovery and Data Mining (PAKDD), 639-647, 2007.
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X. Chen, J. Li, G. Daggard, X. Huang, Finding similar patterns in Microarray data, In Proceedings of Australian Conference on Artificial Intelligence (AI), 1272-1276, 2005.
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F. Khalil, J. Li, and H Wang, Integrating recommendation models for improved Web page prediction accuracy, In Proceedings of the Thirty-First Australasian Computer Science Conference, Wollongong, 2008.
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F. Khalil, J. Li and, H. Wang, Integrating markov model with clustering for predicting Web age accesses, In Proceedings of Australian World Wide Conference, 2007.
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