Cangqi Zhou

According to our database, Cangqi Zhou authored at least 34 papers between 2013 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

A safety fault diagnosis method on industrial intelligent control equipment.

Hanrui Zhang, Qianmu Li, Shunmei Meng, Zhuoran Xu, Chaoxian Lv, Cangqi Zhou

Wirel. Networks, July, 2024

Quintuple-based Representation Learning for Bipartite Heterogeneous Networks.

Cangqi Zhou, Hui Chen, Jing Zhang, Qianmu Li, Dianming Hu

ACM Trans. Intell. Syst. Technol., June, 2024

Active Crowdsourcing for Multilabel Annotation.

Jing Zhang, Ming Wu, Cangqi Zhou, Victor S. Sheng

IEEE Trans. Neural Networks Learn. Syst., March, 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

IEEE Trans Autom. Sci. Eng., January, 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., January, 2024

Heterogeneous Graph Contrastive Learning with Spectral Augmentation.

Jing Zhang, Xiaoqian Jiang, Yingjie Xie, Cangqi Zhou

CoRR, 2024

Timeliness-Selective Incentive Federated Crowdsourcing.

Xiaoqian Jiang, Haiyang Diao, Cangqi Zhou, Jing Zhang

Proceedings of the IEEE International Conference on Web Services, 2024

Multi-level Disentangled Contrastive Learning on Heterogeneous Graphs.

Tong Lin, Cangqi Zhou, Qianmu Li, Dianming Hu

Proceedings of the 2024 16th International Conference on Machine Learning and Computing, 2024

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., July, 2023

Network Intrusion Detection with Edge-Directed Graph Multi-Head Attention Networks.

Xiang Li, Jing Zhang, Yali Yuan, Cangqi Zhou

CoRR, 2023

Hierarchical Graph Contrastive Learning via Debiasing Noise Samples with Adaptive Repelling Ratio.

Peishuo Liu, Cangqi Zhou, Jing Zhang, Qianmu Li, Dianming Hu

Proceedings of the IEEE International Conference on Data Mining, 2023

Multi-Granularity Contrastive Learning for Graph with Hierarchical Pooling.

Peishuo Liu, Cangqi Zhou, Xiao Liu, Jing Zhang, Qianmu Li

Proceedings of the Artificial Neural Networks and Machine Learning, 2023

Heterogeneous Graph Contrastive Learning with Dual Aggregation Scheme and Adaptive Augmentation.

Yingjie Xie, Qi Yan, Cangqi Zhou, Jing Zhang, Dianming Hu

Proceedings of the Web and Big Data - 7th International Joint Conference, 2023

2022

Knowledge Graph Entity Alignment Using Relation Structural Similarity.

Yanhui Peng, Jing Zhang, Cangqi Zhou, Shunmei Meng

J. Database Manag., 2022

Bipartite network embedding with Symmetric Neighborhood Convolution.

Cangqi Zhou, Jing Zhang, Kaisheng Gao, Qianmu Li, Dianming Hu, Victor S. Sheng

Expert Syst. Appl., 2022

AngHNE: Representation Learning for Bipartite Heterogeneous Networks with Angular Loss.

Cangqi Zhou, Hui Chen, Jing Zhang, Qianmu Li, Dianming Hu

Proceedings of the WSDM '22: The Fifteenth ACM International Conference on Web Search and Data Mining, Virtual Event / Tempe, AZ, USA, February 21, 2022

Neural Topic Modeling with Gaussian Mixture Model and Householder Flow.

Cangqi Zhou, Sunyue Xu, Hao Ban, Jing Zhang

Proceedings of the Advances in Knowledge Discovery and Data Mining, 2022

Attributed Graph Clustering with Double Contrastive Projector.

Yuxiang Wang, Cangqi Zhou, Jing Zhang, Qianmu Li

Proceedings of the International Joint Conference on Neural Networks, 2022

End-to-end Modularity-based Community Co-partition in Bipartite Networks.

Cangqi Zhou, Yuxiang Wang, Jing Zhang, Jiqiong Jiang, Dianming Hu

Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022

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

Proceedings of the 18th IEEE International Conference on Automation Science and Engineering, 2022

2021

Word and graph attention networks for semi-supervised classification.

Jing Zhang, Mengxi Li, Kaisheng Gao, Shunmei Meng, Cangqi Zhou

Knowl. Inf. Syst., 2021

Multi-label graph node classification with label attentive neighborhood convolution.

Cangqi Zhou, Hui Chen, Jing Zhang, Qianmu Li, Dianming Hu, Victor S. Sheng

Expert Syst. Appl., 2021

Heterogeneous Graph Embedding Based on Edge-aware Neighborhood Convolution.

Hui Chen, Cangqi Zhou, Jing Zhang, Qianmu Li

Proceedings of the International Joint Conference on Neural Networks, 2021

Topic-Attentive Encoder-Decoder with Pre-Trained Language Model for Keyphrase Generation.

Cangqi Zhou, Jinling Shang, Jing Zhang, Qianmu Li, Dianming Hu

Proceedings of the IEEE International Conference on Data Mining, 2021

HPEMed: Heterogeneous Network Pair Embedding for Medical Diagnosis.

Mengxi Li, Jing Zhang, Lixia Chen, Yu Fu, Cangqi Zhou

Proceedings of the Computer Supported Cooperative Work and Social Computing, 2021

2020

Active Defense by Mimic Association Transmission in Edge Computing.

Shuo Wang, Qianmu Li, Jun Hou, Shunmei Meng, Bo Zhang, Cangqi Zhou

Mob. Networks Appl., 2020

Improving performances of Top-<i>N</i> recommendations with co-clustering method.

Liang Feng, Qianchuan Zhao, Cangqi Zhou

Expert Syst. Appl., 2020

Gaussian Mixture Variational Autoencoder for Semi-Supervised Topic Modeling.

Cangqi Zhou, Hao Ban, Jing Zhang, Qianmu Li, Yinghua Zhang

IEEE Access, 2020

Embedding-Based Entity Alignment Using Relation Structural Similarity.

Yanhui Peng, Jing Zhang, Cangqi Zhou, Jian Xu

Proceedings of the 2020 IEEE International Conference on Knowledge Graph, 2020

2019

Semi-supervised Graph Embedding for Multi-label Graph Node Classification.

Kaisheng Gao, Jing Zhang, Cangqi Zhou

Proceedings of the Web Information Systems Engineering - WISE 2019, 2019

An Active Defense Model in Edge Computing Based on Network Topology Mimetic Correlation.

Shuo Wang, Qianmu Li, Shunmei Meng, Bo Zhang, Cangqi Zhou

Proceedings of the Mobile Computing, Applications, and Services, 2019

An efficient method to find communities in <i>K</i>-partite networks.

Liang Feng, Qianchuan Zhao, Cangqi Zhou

Proceedings of the ASONAM '19: International Conference on Advances in Social Networks Analysis and Mining, 2019

2014

Efficient Time Series Clustering and Its Application to Social Network Mining.

Cangqi Zhou, Qianchuan Zhao

J. Intell. Syst., 2014

2013

An angle-based dissimilarity for accelerating the clustering of dynamic data in networks.

Cangqi Zhou, Qianchuan Zhao, Ruixi Yuan

Proceedings of 10th IEEE International Conference on Networking, Sensing and Control, 2013