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西南大学计算机与信息科学学院导师教师师资介绍简介-中级(讲师,工程师,管理等)

本站小编 Free考研考试/2021-10-05



姓名: 程鹏 性别: 男
学历: 博士 职称: 讲师
部门:
电话:

邮件地址: chengp@swu.edu.cn


研究方向: 数据挖掘隐私保护,进化多目标优化







个人简介
不唯洋,不唯书,不唯学历、职称、SCI、影响因子... ...,只唯实,真才实学的‘实’。
更多的去关注在研究领域的贡献是什么?解决了什么样的问题?


教学情况


科研情况
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.

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