Journal paper：
[1] P. Cheng, J. F. Roddick, S.-C. Chu, and C.-W. Lin, “Privacy preservation through a greedy, distortion-based rule hiding method,” Applied Intelligence, vol. 44, no. 2, pp. 295-306, 2016.
[2] P. Cheng, I. Lee, C.-W. Lin, and J.-S. Pan, “Association Rule Hiding Based on Evolutionary Multi-objective Optimization,” Intelligent Data Analysis, vol. 20, no. 3, 2016 (To appear).
[3] P. Cheng, I. Lee, J.-S. Pan, C.-W. Lin, and J. F. Roddick, “Hide Association Rules with Fewer Side Effects,” IEICE Transactions on Information and System, vol. E98-D, no. 10, pp. 1788-1798, 2015.
Conference paper:
[1] P. Cheng, I. Lee, and et al., “BRBA: a Blocking-based Association Rule Hiding Method,” in Thirtieth AAAI Conference on Artificial Intelligence (AAAI), 2016. (Accepted) (Poster)
[2] P. Cheng, S.-C. Chu, C.-W. Lin, and J. F. Roddick, "Distortion-Based Heuristic Sensitive Rule Hiding Method–The Greedy Way," Modern Advances in Applied Intelligence, Springer, 2014.
[3] P. Cheng, and J.-S. Pan, “Association Rule Hiding Based on Evolutionary Multi-Objective Optimization by Removing Items,” in Twenty-Eighth AAAI Conference on Artificial Intelligence (AAAI), 2014. (Poster)
[4] P. Cheng, and J.-S. Pan, “Use EMO to Protect Sensitive Knowledge in Association Rule Mining by Adding Items,” in Proceedings of the 2014 Conference Companion on Genetic and Evolutionary Computation (ACM GECCO), 2014.
[5] P. Cheng, and J.-S. Pan, “Completely Hide Sensitive Association Rules Using EMO by Deleting Transactions,” in Proceedings of the 2014 Conference Companion on Genetic and Evolutionary Computation (ACM GECCO), 2014.
[6] P. Cheng, J.-S. Pan, and C.-W. Lin, “Privacy Preserving Association Rule Mining Using Binary Encoded NSGA-II,” in Proceedings of the 18th Pacific-Asia Conference on Knowledge Discovery and Data Mining Workshop (PAKDD Workshop), 2014.
|
