研究组论文开放源码&数据@Github：https://github.com/GDM-SCNU

[1] Chaobo He, Yulong Zheng, Xiang Fei, Hanchao Li, Zeng Hu, Yong Tang. Boosting nonnegative matrix factorization based community detection with graph attention auto-encoder.IEEE Transactions on Big Data, 2022:8(4):968-981. (代码&数据)

[2] Chaobo He, Yulong Zheng, Junwei Cheng, Yong Tang, Guohua Chen, Hai Liu. Semi-supervised overlapping community detection in attributed graph with graph convolutional autoencoder.Information Sciences, 2022,608:1464-1479. (代码&数据) 

[3] Community preserving adaptive graph convolutional networks for link prediction in attributed networks. Submitted to Knowledge-Based Systems. (代码&数据) 

[4] Detecting communities with multiple topics in attributed networks via self-supervised adaptive graph convolutional network. Submitted to Information Fusion. (代码&数据)  

[5] 动态属性网络的语义社区发现及演化分析方法.计算机研究与发展（一审）. (代码&数据)   

[6] 一种融合节点变化信息的动态社区发现方法.电子学报（三审）. (代码&数据)    

[7] Junwei Cheng, Yong Tang, Chaobo He, Kunlin Han, Ying Li and Jinhui Wei. Community detection in attributed networks via adaptive deep nonnegative matrix factorization.  Submitted to Neural Computing and Applications. Under the 2nd round review,Minor Revision. (代码&数据)    

[8] Junwei Cheng, Yong Tang, Kunlin Han, Xingyu, Liu, Chaobo He.Community detection beyond topology structure in multiplex Networks. Submitted to Expert Systems with Applications. (代码&数据） 

[9] Junwei Cheng, Yong Tang, Kunlin Han, Yulong Zheng, Chaobo He. When Graph Neural Networks Meet Deep Nonnegative Matrix Factorization: An Encoder and Decoder-like Method for Community Detection. Submitted to IEEE Transactions on Network Science and Engineering.