An angle-based dissimilarity for accelerating the clustering of dynamic data in networks. - Cangqi Zhou; Qianchuan Zhao; Ruixi Yuan (ICNSC, 2013)

Efficient Time Series Clustering and Its Application to Social Network Mining. - Cangqi Zhou; Qianchuan Zhao (J. Intell. Syst., 2014)

An efficient method to find communities in K-partite networks. - Liang Feng; Qianchuan Zhao; Cangqi Zhou (ASONAM, 2019)

An Active Defense Model in Edge Computing Based on Network Topology Mimetic Correlation. - Shuo Wang 017; Qianmu Li; Shunmei Meng; Bo Zhang; Cangqi Zhou (MobiCASE, 2019)

Semi-supervised Graph Embedding for Multi-label Graph Node Classification. - Kaisheng Gao; Jing Zhang 015; Cangqi Zhou (WISE, 2019)

Embedding-Based Entity Alignment Using Relation Structural Similarity. - Yanhui Peng; Jing Zhang 015; Cangqi Zhou; Jian Xu 009 (ICKG, 2020)

Gaussian Mixture Variational Autoencoder for Semi-Supervised Topic Modeling. - Cangqi Zhou; Hao Ban; Jing Zhang 015; Qianmu Li; Yinghua Zhang (IEEE Access, 2020)

Improving performances of Top-N recommendations with co-clustering method. - Liang Feng; Qianchuan Zhao; Cangqi Zhou (Expert Syst. Appl., 2020)

Active Defense by Mimic Association Transmission in Edge Computing. - Shuo Wang 017; Qianmu Li; Jun Hou 002; Shunmei Meng; Bo Zhang; Cangqi Zhou (Mob. Networks Appl., 2020)

HPEMed: Heterogeneous Network Pair Embedding for Medical Diagnosis. - Mengxi Li; Jing Zhang; Lixia Chen; Yu Fu; Cangqi Zhou (ChineseCSCW (2), 2021)

Topic-Attentive Encoder-Decoder with Pre-Trained Language Model for Keyphrase Generation. - Cangqi Zhou; Jinling Shang; Jing Zhang 015; Qianmu Li; Dianming Hu (ICDM, 2021)

Heterogeneous Graph Embedding Based on Edge-aware Neighborhood Convolution. - Hui Chen; Cangqi Zhou; Jing Zhang 015; Qianmu Li (IJCNN, 2021)

Multi-label graph node classification with label attentive neighborhood convolution. - Cangqi Zhou; Hui Chen; Jing Zhang 015; Qianmu Li; Dianming Hu; Victor S. Sheng (Expert Syst. Appl., 2021)

Word and graph attention networks for semi-supervised classification. - Jing Zhang 015; Mengxi Li; Kaisheng Gao; Shunmei Meng; Cangqi Zhou (Knowl. Inf. Syst., 2021)

Optimal Model of Cloud-Based Multi-Agent System for Trade-off Between Trustworthiness of Data and Cost of Data Usage. - Chen Hou; Cangqi Zhou; Chu-Ge Wu; Rui Cong; Kun Li (CASE, 2022)

End-to-end Modularity-based Community Co-partition in Bipartite Networks. - Cangqi Zhou; Yuxiang Wang; Jing Zhang 015; Jiqiong Jiang; Dianming Hu (CIKM, 2022)

Attributed Graph Clustering with Double Contrastive Projector. - Yuxiang Wang; Cangqi Zhou; Jing Zhang 015; Qianmu Li (IJCNN, 2022)

Neural Topic Modeling with Gaussian Mixture Model and Householder Flow. - Cangqi Zhou; Sunyue Xu; Hao Ban; Jing Zhang 015 (PAKDD (2), 2022)

AngHNE: Representation Learning for Bipartite Heterogeneous Networks with Angular Loss. - Cangqi Zhou; Hui Chen; Jing Zhang 015; Qianmu Li; Dianming Hu (WSDM, 2022)

Bipartite network embedding with Symmetric Neighborhood Convolution. - Cangqi Zhou; Jing Zhang 015; Kaisheng Gao; Qianmu Li; Dianming Hu; Victor S. Sheng (Expert Syst. Appl., 2022)

Knowledge Graph Entity Alignment Using Relation Structural Similarity. - Yanhui Peng; Jing Zhang 015; Cangqi Zhou; Shunmei Meng (J. Database Manag., 2022)

Heterogeneous Graph Contrastive Learning with Dual Aggregation Scheme and Adaptive Augmentation. - Yingjie Xie; Qi Yan; Cangqi Zhou; Jing Zhang; Dianming Hu (APWeb/WAIM (4), 2023)

Multi-Granularity Contrastive Learning for Graph with Hierarchical Pooling. - Peishuo Liu; Cangqi Zhou; Xiao Liu 043; Jing Zhang 015; Qianmu Li (ICANN (4), 2023)

Hierarchical Graph Contrastive Learning via Debiasing Noise Samples with Adaptive Repelling Ratio. - Peishuo Liu; Cangqi Zhou; Jing Zhang 015; Qianmu Li; Dianming Hu (ICDM, 2023)

Network Intrusion Detection with Edge-Directed Graph Multi-Head Attention Networks. - Xiang Li; Jing Zhang 015; Yali Yuan; Cangqi Zhou (CoRR, 2023)

A Simulation-Based Primal-Dual Approach for Constrained V2G Scheduling in a Microgrid of Building. - Qilong Huang; Li Yang; Qing-Shan Jia; Yaowen Qi; Cangqi Zhou; Xiaohong Guan (IEEE Trans Autom. Sci. Eng., 2023)

Multi-level Disentangled Contrastive Learning on Heterogeneous Graphs. - Tong Lin; Cangqi Zhou; Qianmu Li; Dianming Hu (ICMLC, 2024)

Timeliness-Selective Incentive Federated Crowdsourcing. - Xiaoqian Jiang; Haiyang Diao; Cangqi Zhou; Jing Zhang 015 (ICWS, 2024)

Heterogeneous Graph Contrastive Learning with Spectral Augmentation. - Jing Zhang 015; Xiaoqian Jiang; Yingjie Xie; Cangqi Zhou (CoRR, 2024)

Cache Control of Edge Computing System for Tradeoff Between Delays and Cache Storage Costs. - Chen Hou; Cangqi Zhou; Qilong Huang; Chao-Bo Yan (IEEE Trans Autom. Sci. Eng., 2024)

Optimization of Cloud-Based Multi-Agent System for Trade-Off Between Trustworthiness of Data and Cost of Data Usage. - Chen Hou; Cangqi Zhou; Chu-Ge Wu; Rui Cong; Kun Li 013 (IEEE Trans Autom. Sci. Eng., 2024)

Active Crowdsourcing for Multilabel Annotation. - Jing Zhang 015; Ming Wu 004; Cangqi Zhou; Victor S. Sheng (IEEE Trans. Neural Networks Learn. Syst., 2024)

Quintuple-based Representation Learning for Bipartite Heterogeneous Networks. - Cangqi Zhou; Hui Chen; Jing Zhang 015; Qianmu Li; Dianming Hu (ACM Trans. Intell. Syst. Technol., 2024)

A safety fault diagnosis method on industrial intelligent control equipment. - Hanrui Zhang 002; Qianmu Li; Shunmei Meng; Zhuoran Xu; Chaoxian Lv; Cangqi Zhou (Wirel. Networks, 2024)

Open-World Knowledge Augmentation for Zero-Shot Information Extraction in LLMs. - Haijiang Li; Cangqi Zhou; Jing Zhang; Dianming Hu (ICIC (23), 2025)

Learning From Crowds Using Graph Neural Networks With Attention Mechanism. - Jing Zhang 015; Ming Wu 004; Zeyi Sun 001; Cangqi Zhou (IEEE Trans. Big Data, 2025)