Representative Papers:
[1] Q. Zhao, P. Wu, G. Liu, D. An, J. Lian*, and M. Zhou, “Sociological-Theories-Based Multi-Topic Self-Supervised Recommendation,” IEEE Transactions on Neural Networks and Learning Systems, Accpeted, 2024. (SCI, JCR Q1, Top Journal)
[2] Q. Zhao, C. Wang, P. Wang, M. Zhou, and C. Jiang*, “A Novel Method on Information Recommendation via Hybrid Similarity,” IEEE Transactions on Systems, Man, and Cybernetics: Systems, vol. 48, no. 3, pp. 448-459, 2018. (SCI, JCR Q1, Top Journal)
[3] D. Qin, J. Yu, G. Zou, R. Yong, Q. Zhao*, and B. Zhang*, “A Novel Combined Prediction Scheme Based on CNN and LSTM for Urban PM2.5 Concentration,” IEEE Access, vol. 7, pp. 20050-20059, 2019. (SCI, Cited over 250 times)
[4] Q. Zhao, J. Huang, G. Liu*, Y. Miao, and P. Wang*, “A Multiinterest and Social Interest-Field Framework for Financial Security,” IEEE Transactions on Computational Social Systems, vol. 11, no. 2, pp. 1685-1695, 2024. (SCI, JCR Q1, Top Journal)
[5] J. Lian, S. Wu, S. Huang, and Q. Zhao*, “A Novel Sequence-to-Sequence Based Deep Learning Model for Satellite Cloud Image Time Series Prediction,” Atmospheric Research, vol. 306, pp. 107457, 2024. (SCI, JCR Q1, Top Journal)
2024:
[1] Q. Zhao, J. Huang, G. Liu*, Y. Miao, and P. Wang*, “A Multiinterest and Social Interest-Field Framework for Financial Security,” IEEE Transactions on Computational Social Systems, vol. 11, no. 2, pp. 1685-1695, 2024. (SCI, JCR Q1, Top Journal)
[2] Q. Zhao, F. Yang, D. An, and J. Lian*, “Modeling Structured Dependency Tree with Graph Convolutional Networks for Aspect-level Sentiment Classification,” Sensors, vol. 24, no. 2, pp. 418, 2024. (SCI)
[3] Q. Zhao, C. Yu, J. Huang, J. Lian, and D. An*, “Sentiment Analysis Based on Heterogeneous Multi-relation Signed Network,” Mathematics, vol. 12, no. 2, pp. 331, 2024. (SCI, JCR Q1)
[4] Q. Zhao, Y. Miao, D. An, J. Lian*, and M. Li, “HGNN-QSSA: Heterogeneous Graph Neural Networks with Quantitative Sampling and Structure-aware Attention,” IEEE Access, vol. 12, pp. 25512-25524, 2024. (SCI)
[5] Q. Zhao, Y. Miao, J. Lian, X. Li, and D. An*, “Louvain-Based Fusion of Topology and Attribute Structure of Social Networks,” Computing and Informatics, vol. 43, no.1, pp. 94-125, 2024. (SCI)
[6] C. Yu, X. Lin, Y. Yan, Y. Cheng, H. Wang, Y. Huang, W. Zhao, L. Liu, Q. Zhao*, J. Wang*, and L. Zhang*, “AbDPP: Target-oriented Antibody Design with Pre-training and Prior Biological Structure Knowledge,” Proteins: Structure, Function, and Bioinformatics, vol. 92, no. 10, pp. 1147-1160, 2024. (SCI)
[7] J. Lian, S. Wu, S. Huang, and Q. Zhao*, “A Novel Sequence-to-Sequence Based Deep Learning Model for Satellite Cloud Image Time Series Prediction,” Atmospheric Research, vol. 306, pp. 107457, 2024. (SCI, JCR Q1, Top Journal)
[8] Q. Zhao, P. Wu, J. Lian, D. An*, and M. Li, “TaneNet: Two-level Attention Network Based on Emojis for Sentiment Analysis,” IEEE Access, vol. 12, pp. 86106-86119, 2024. (SCI)
[9] Q. Zhao, P. Wu, G. Liu, D. An, J. Lian*, and M. Zhou, “Sociological-Theories-Based Multi-Topic Self-Supervised Recommendation,” IEEE Transactions on Neural Networks and Learning Systems, Accpeted, 2024. (SCI, JCR Q1, Top Journal)
[10] Q. Zhao, G. Yang, Y. Miao, J. Lian, H. Qi*, and Z. Kou, “Adaptive Sampling-based Heterogeneous Graph Enhancement,” Computing and Informatics, Minor Revision. (SCI)
[11] D. An, Z. Pan, Q. Zhao, W. Liu, and J. Liu*, “Unsupervised Graph Structure Learning Based on Optimal Graph Topology Modeling and Adaptive Data Augmentation,” Mathematics, vol. 12, no. 13, pp. 1991, 2024. (SCI, JCR Q1)
[12] D. An, Y. Yang, W. Liu, Q. Zhao, J. Liu, H. Qi, and J. Lian*, “A Secure GNN Training Framework for Partially Observable Graph,” Electronics, vol. 13, no. 14, pp. 2721, 2024. (SCI)
2023:
[1] Q. Zhao, G. Liu, F. Yang, R. Yang*, Z. Kou, and D. Wang, “Self-Supervised Signed Graph Attention Network for Social Recommendation,” in Proceedings of the International Joint Conference on Neural Networks, pp. 1-9, 2023. (CCF-C)
[2] H. Huang, P. Wang*, Z. Zhang, and Q. Zhao, “A Spatio-Temporal Attention-based GCN for Anti-Money Laundering Transaction Detection,” in Proceedings of the 19th International Conference on Advanced Data Mining and Applications, pp. 634-648, 2023. (CCF-C)
2022:
[1] Q. Zhao, Z. Zhou, J. Li, S. Jia, and J. Pan*, “Time-Dependent Prediction of Microblog Propagation Trends Based on Group Features,” Electronics, vol. 11, no. 16, pp. 2585, 2022. (SCI)
[2] N. Fu, Q. Zhao*, Y. Miao, B. Zhang, and D. Wang, “A Representation Learning Method of Graph Convolutional Network Based on Structure Enhancement,” Computing and Informatics, vol. 41, no. 6, pp. 1563–1588, 2022. (SCI)
[3] J. Pan, H. Li, J. Teng, Q. Zhao*, and M. Li*, “Dynamic Network Representation Learning Method Based on Improved GRU Network,” Computing and Informatics, vol. 41, no. 6, pp. 1491–1509, 2022. (SCI)
Before 2021:
[1] Q. Zhao*, C. Wang, and C. Jiang, “HSim: A Novel Method on Similarity Computation by Hybrid Measure,” in Proceedings of IEEE International Conference on Information and Communication Systems (ICICS), pp. 160-165, 2015. (EI)
[2] 赵勤, 王成, 王鹏伟. 一种基于社区分类的社交网络用户推荐方法[J]. 计算机科学, 2016, 43(5): 198-203. (CCF-B)
[3] Q. Zhao, Y. He, C. Jiang*, P. Wang, M. Qi, and M. Li, “Integration of Link and Semantic Relations for Information Discovery and Recommendation,” Computing and Informatics, vol. 35, no. 1, pp. 30-54, 2016. (SCI)
[4] B. Zhang, H. Zhang, M. Li*, Q. Zhao, and J. Huang, “Trust Traversal: A Trust Link Detection Scheme in Social Network,” Computer Networks, vol. 120, pp. 105-125, 2017. (SCI)
[5] B. Zhang, C. Mu, Q. Zhao*, Z. Peng, J. Ding, and B. Liu, “A Multidimensional Comprehensive Recommendation Method Based on Social Network,” in Proceedings of 5th International Conference on Advanced Cloud and Big Data (CBD), Shanghai, China, 2017.08.13-08.16. (EI)
[6] 张波, 金玉鹏, 张倩, 赵勤, 王娇燕. 试论一种新型在线教育资源大数据组织框架, 中国电化教育, 2018 (3): 41-46. (CSSCI)
[7] Q. Zhao, C. Wang, P. Wang, M. Zhou, and C. Jiang*, “A Novel Method on Information Recommendation via Hybrid Similarity,” IEEE Transactions on Systems, Man, and Cybernetics: Systems, vol. 48, no. 3, pp. 448-459, 2018. (SCI, 中科院一区, TOP期刊)
[8] D. Qin, J. Yu, G. Zou, R. Yong, Q. Zhao*, and B. Zhang*, “A Novel Combined Prediction Scheme Based on CNN and LSTM for Urban PM2.5 Concentration,” IEEE Access, vol. 7, pp.20050-20059, 2019. (SCI)
[9] W. Liu, P. Wang*, Y. Meng, Q. Zhao*, C. Zhao, and Z. Zhang, “A Novel Model for Optimizing Selection of Cloud Instance Types,” IEEE Access, vol. 7, pp. 120508 – 120521, 2019. (SCI)
[10] 秦东明, 丁志军, 金玉鹏, 赵勤*. 基于自编码网络的空气污染物浓度预测[J]. 同济大学学报: 自然科学版, 2019, 47(5): 681-687. (EI)
[11] S. Huang, Q. Zhao*, X. Xu, B. Zhang*, and D. Wang, “Emojis-Based Recurrent Neural Network for Chinese Microblogs Sentiment Analysis,” in Proceedings of IEEE International Conference on Service Operations and Logistics, and Informatics (SOLI), pp. 59-64, November 2019. (EI)
[12] 秦东明, 喻剑, 张波, 赵勤*. 基于分布式无共享架构的海量数据并行查询平台[J]. 计算机科学, 2019, 46(4): 44-49. (CCF-B)
[13] B. Zhang, L. Zhang, C. Mu, Q. Zhao, Q. Song, and X. Hong*, “A Most Influential Node Group Discovery Method for Influence Maximization in Social Networks: A Trust-Based Perspective,” Data & Knowledge Engineering, vol. 121, pp. 71–87, 2019. (SCI)
[14] C. Wang, H. Zhu, C. Wang, Q. Zhao, and B. Zhang, “Transport Complexity of Data Dissemination in Large-Scale Online Social Networks,” in Proceedings of the ACM Turing Celebration Conference-China, pp. 1–5, 2019. (EI)
[15] G. Zou, B. Zhang, R. Yong, D. Qin, and Q. Zhao, “FDN-learning: Urban PM2. 5-concentration Spatial Correlation Prediction Model Based on Fusion Deep Neural Network,” Big Data Research, vol. 26, pp. 100269, 2021. (SCI)