会议论文

  1. Liu, X., Shen, C., Fan, Y., Liu, X., Zhou, Y., & Guan, X. (2018, December). A Co-Evolutionary Model for Inferring Online Social Network User Behaviors. In 2018 International Conference on Security, Pattern Analysis, and Cybernetics (SPAC) (pp. 85-90). IEEE. (Best Student Paper Award)
  2.  Liu, X., Zhou, Y., Hu, C., Guan, X., & Leng, J. (2014, April). Detecting community structure for undirected big graphs based on random walks. In Proceedings of the 23rd International Conference on World Wide Web (pp. 1151-1156). (CCF A, Workshop on Big Graph Minng)
  3. Liu, X., Zhou, Y., Hu, C., Guan, X., & Sun, X. (2015, July). A feasible graph partition framework for random walks implemented by parallel computing in big graph. In 2015 34th Chinese Control Conference (CCC) (pp. 4986-4991). IEEE.
期刊论文

  1.  Liu X, Shen C, Wang W, Guan X. CoEvil: A Co-Evolutionary Model for Crime Inference Based on Fuzzy Rough Feature Selection. IEEE Transactions on Fuzzy Systems. 2019 Sep 6. (SCI  IF 8.759, CCF B );
  2. Liu, X., Shen, C., Guan, X., & Zhou, Y. (2018). Digger: Detect Similar Groups in Heterogeneous Social Networks. ACM Transactions on Knowledge Discovery from Data (TKDD)13(1), 1-27. (SCI IF 1.895, CCF B)
  3. Liu, X., Shen, C., Guan, X., & Zhou, Y. (2018). We know who you are: Discovering similar groups across multiple social networks. IEEE Transactions on Systems, Man, and Cybernetics: Systems (SCI  IF 7.351, CCF C )
  4. Liu, X., Zhou, Y., Guan, X., & Shen, C. (2017). A feasible graph partition framework for parallel computing of big graph. Knowledge-Based Systems134, 228-239. (SCI  IF 5.101, CCF C);
  5. Liu, X., Zhou, Y., Hu, C., & Guan, X. (2016). MIRACLE: A multiple independent random walks community parallel detection algorithm for big graphs. Journal of Network and Computer Applications70, 89-101. (SCI IF 5.273, CCF C);
  6. 周亚东, 刘晓明, 杜友田, 管晓宏, & 刘霁. (2015). 一种网络话题的内容焦点迁移识别方法. 计算机学报38(2), 261-271. 
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