Research output per year
Research output per year
- 14 results
Search results
-
2024
A comprehensive survey on community detection with deep learning
Su, X., Xue, S., Liu, F., Wu, J., Yang, J., Zhou, C., Hu, W., Paris, C., Nepal, S., Jin, D., Sheng, Q. Z. & Yu, P. S., Apr 2024, In: IEEE Transactions on Neural Networks and Learning Systems. 35, 4, p. 4682-4702 21 p.Research output: Contribution to journal › Article › peer-review
203 Citations (Scopus) -
Graph anomaly detection with few labels: a data-centric approach
Ma, X., Li, R., Liu, F., Ding, K., Yang, J. & Wu, J., 2024, KDD '24: proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining. New York: Association for Computing Machinery, p. 2153–2164 12 p.Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding contribution › peer-review
Open AccessFile1 Citation (Scopus)174 Downloads (Pure) -
Rethinking unsupervised graph anomaly detection with deep learning: residuals and objectives
Ma, X., Liu, F., Wu, J., Yang, J., Xue, S. & Sheng, Q. Z., 18 Nov 2024, (E-pub ahead of print) In: IEEE Transactions on Knowledge and Data Engineering.Research output: Contribution to journal › Article › peer-review
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2022
DAGAD: Data Augmentation for Graph Anomaly Detection
Liu, F., Ma, X., Wu, J., Yang, J., Xue, S., Beheshti, A., Zhou, C., Peng, H., Sheng, Q. Z. & Aggarwal, C. C., 2022, 22nd IEEE International Conference on Data Mining ICDM 2022: proceedings. Zhu, X., Ranka, S., Thai, M. T., Washio, T. & Wu, X. (eds.). Piscataway, NJ: Institute of Electrical and Electronics Engineers (IEEE), p. 259-268 10 p.Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding contribution › peer-review
26 Citations (Scopus) -
eRiskCom: an e-commerce risky community detection platform
Liu, F., Li, Z., Wang, B., Wu, J., Yang, J., Huang, J., Zhang, Y., Wang, W., Xue, S., Nepal, S. & Sheng, Q. Z., Sept 2022, In: VLDB Journal. 31, 5, p. 1085-1101 17 p.Research output: Contribution to journal › Article › peer-review
15 Citations (Scopus) -
2020
Deep learning for community detection: progress, challenges and opportunities
Liu, F., Xue, S., Wu, J., Zhou, C., Hu, W., Paris, C., Nepal, S., Yang, J. & Yu, P. S., 2020, Proceedings of the 29th International Joint Conference on Artificial Intelligence, IJCAI 2020. Bessiere, C. (ed.). California: International Joint Conferences on Artificial Intelligence, p. 4981-4987 7 p. (IJCAI International Joint Conference on Artificial Intelligence; vol. 2021-January).Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding contribution › peer-review
Open Access150 Citations (Scopus) -
Detecting the evolving community structure in dynamic social networks
Liu, F., Wu, J., Xue, S., Zhou, C., Yang, J. & Sheng, Q., Mar 2020, In: World Wide Web. 23, 2, p. 715-733 19 p.Research output: Contribution to journal › Article › peer-review
48 Citations (Scopus) -
Microcluster-based incremental ensemble learning for noisy, nonstationary data streams
Liu, S., Xue, S., Liu, F., Cheng, J., Li, X., Kong, C. & Wu, J., 2020, In: Complexity. 2020, 12 p., 6147378.Research output: Contribution to journal › Article › peer-review
Open AccessFile3 Citations (Scopus)43 Downloads (Pure) -
2019
Evolutionary community detection in dynamic social networks
Liu, F., Wu, J., Zhou, C. & Yang, J., 1 Jul 2019, 2019 International Joint Conference on Neural Networks, IJCNN 2019. Piscataway, NJ: Institute of Electrical and Electronics Engineers (IEEE), Vol. 2019-July. p. 1-7 7 p. N-20102Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding contribution › peer-review
21 Citations (Scopus) -
2018
Inferring infection rate based on observations in complex networks
Su, Z., Liu, F., Gao, C., Gao, S. & Li, X., Feb 2018, In: Chaos, Solitons and Fractals. 107, p. 170-176 7 p.Research output: Contribution to journal › Article › peer-review
3 Citations (Scopus) -
2017
A hybrid evolutionary algorithm for community detection
Liu, F., Chen, Z., Cui, Y., Liu, C., Li, X. & Gao, C., 2017, 2017 IEEE/WIC/ACM International Conference on Web Intelligence WI 2017: proceedings. New York: Association for Computing Machinery, p. 469-475 7 p.Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding contribution › peer-review
3 Citations (Scopus) -
An enhanced particle swarm optimization based on Physarum model for community detection
Chen, Z., Liu, F., Gao, C., Li, X. & Zhang, Z., 2017, Advances in swarm intelligence: 8th International Conference, ICSI 2017, Fukuoka, Japan, July 27 – August 1, 2017, proceedings, Part II. Tan, Y., Takagi, H., Shi, Y. & Niu, B. (eds.). Cham: Springer, Springer Nature, p. 99-108 10 p. (Lecture Notes in Computer Science; vol. 10386).Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding contribution › peer-review
2 Citations (Scopus) -
A novel strategy of initializing the population size for ant colony optimization algorithms in TSP
Liu, F., Zhong, J., Liu, C., Gao, C. & Li, X., 2017, ICNC-FSKD 2017: 13th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery. Liu, Y., Zhao, L., Cai, G., Xiao, G., Li, K. & Wang, L. (eds.). Piscataway, NJ: Institute of Electrical and Electronics Engineers (IEEE), p. 249-253 5 p.Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding contribution › peer-review
8 Citations (Scopus) -
Robustness analysis of the complex network
Liang, M., Liu, F., Gao, C. & Zhang, Z., 2017, Proceedings of 2017 IEEE 6th Data Driven Control and Learning Systems Conference (DDCLS'17). Sun, M. & Gao, H. (eds.). Piscataway, NJ: Institute of Electrical and Electronics Engineers (IEEE), p. 638-643 6 p.Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding contribution › peer-review
5 Citations (Scopus)