秦科
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1. 招生信息：https://yjsjy.uestc.edu.cn/gmis/jcsjgl/dsfc/dsgrjj/11422?yxsh=90
2. Paper List（Partial， Updated on 2025.02.09）
Dong Y, Qin K, Ke P, et al. Cross-graph Knowledge Exchange for Personalized Response Generation in Dialogue Systems[J]. IEEE Internet of Things Journal, 2025. （中科院JCR 1区）
Zakari R Y, Owusu J W, Qin K, et al. Seeing and Reasoning: A Simple Deep Learning Approach to Visual Question Answering[J]. Big Data Mining and Analytics, 2025, 8(2): 458-478. （中科院JCR 1区）
Zakari R Y, Owusu J W, Qin K, et al. VQA and visual reasoning: An overview of approaches, datasets, and future direction[J]. Neurocomputing, 2025: 129345. （中科院JCR 2区）
Qiu J, Zhu T, Qin K, et al. The interaction network and potential clinical effectiveness of dimensional psychopathology phenotyping based on EMR: a Bayesian network approach[J]. BMC psychiatry, 2025, 25(1): 81.
Dong Y, Qin K, Liang S, et al. GKA-GPT: Graphical knowledge aggregation for multiturn dialog generation[J]. Knowledge-Based Systems, 2025, 309: 112763. （中科院JCR 1区）
Yuezhou Dong, Ke Qin, Shuang Liang, Hierarchical Knowledge Aggregation for Personalized Response Generation in Dialogue Systems, CCF International Conference on Natural Language Processing and Chinese Computing (NLPCC2024). 2024, 29-42
Li Muquan, Dongyang Zhang, Tao He, Xiurui Xie, Yuan-Fang Li, and Ke Qin. "Towards Effective Data-Free Knowledge Distillation via Diverse Diffusion Augmentation." In Proceedings of the 32nd ACM International Conference on Multimedia (ACM MM2024), pp. 4416-4425. 2024. （CCF A会议）
Miao, Li-Teng, Yi-Zhuo Ma, Ke Qin, Rui-Ting Dai, and Ahmad Raza. "ACT-R Theory Can Promote Personality Analysis of Social Network Subjects." In International Conference on Intelligent Computing (ICIC2024), pp. 15-26. Singapore: Springer Nature Singapore, 2024.
Dai, L. and Qin, K., 2024, June. ToFC: Tree-of-Fact with Continued Best-First Search for Commonsense Reasoning. In 2024 International Joint Conference on Neural Networks (IJCNN2024) (pp. 1-8). IEEE.
Ma, Y., Qin, K. and Liang, S., 2024, June. Beta-LR: Interpretable Logical Reasoning based on Beta Distribution. In Findings of the Association for Computational Linguistics: NAACL 2024 (pp. 1945-1955). （CCF B会议）
Wang H, Zhang D, Liu G, Huang L, Qin K. Enhancing relation extraction using multi-task learning with SDP evidence. Information Sciences. 2024, 670:120610. （中科院JCR 1区）
Zhang D, Liang S, He T, Shao J, Qin Ke. CVIformer: Cross-View Interactive Transformer for Efficient Stereoscopic Image Super-Resolution[J]. IEEE Transactions on Emerging Topics in Computational Intelligence, 2024. （中科院JCR 2区）
Hailin Wang, Dan Zhang, Guisong Liu, Li Huang, Ke Qin， Enhancing relation extraction using multi-task learning with SDP evidence， Information Sciences， 670, 2024, 120610. （中科院JCR 1区）
Liu C, Zhang D, Qin K. Knowledge Distillation for Single Image Super-Resolution via Contrastive Learning. InProceedings of the 2024 International Conference on Multimedia Retrieval (ICMR2024), 2024 May 30 (pp. 1079-1083). （CCF B会议）
Dai L, Qin K. ToFC: Tree-of-Fact with Continued Best-First Search for Commonsense Reasoning[C], 2024 International Joint Conference on Neural Networks (IJCNN2024). 2024: 1-8.
Zeng X, Bai Z, Qin K, et al. EiGC: An Event-Induced Graph with Constraints for Event Causality Identification[J]. Electronics, 2024, 13(23): 4608.
Qiu J, Yu C, Kuang Y, Zhu T, Qin K, Zhang W. Association between psychiatric symptoms with multiple peripheral blood sample test: a 10-year retrospective study[J]. Frontiers in Psychiatry, 2024, 15: 1481006.
Qiuyi Qi, Tuo Shi, Ke Qin and Guangchun Luo, Completion Time Optimization in UAV-Relaying-Assisted MEC Networks with Moving Users, IEEE Transactions on Consumer Electronics, doi: 10.1109/TCE.2023.3278470, 2023. （中科院JCR 2区）
Wang H, Qin K , Duan G, et al. Denoising Graph Inference Network for Document-Level Relation Extraction[J]. Big Data Mining and Analytics, 2023, 6(2): 248-262. （中科院JCR 1区）
Wang H, Qin K, Lu G, et al. Deep neural network-based relation extraction: an overview[J]. Neural Computing and Applications, 2022: 1-21. （中科院JCR 2区）
Wang H, Qin K, Lu G, et al. Document-level relation extraction using evidence reasoning on RST-GRAPH[J]. Knowledge-Based Systems, 2021: 107274.link （中科院JCR 1区）
Yin J, Wang J, Jiang J, Sun Y, Chen X, Qin Ke. Research on the Construction and Application of Breast Cancer-specific Database System Based on Full Data Lifecycle[J]. Frontiers in Public Health, 2021, 9: 936. link
Duan G, Yang H, Qin K , et al. Improving Neural Machine Translation Model with Deep Encoding Information[J]. Cognitive Computation, 2021: 1-9. link （中科院JCR 2 区）
Min S, Gao Z, Peng J, Qin K et al. STGSN-A Spatial-Temporal Graph Neural Network framework for time-evolving social networks[J]. Knowledge-Based Systems, 106746.Link （中科院JCR 1区）
Ainam J P, Qin K, Owusu J W, Lu Guoming. Unsupervised domain adaptation for person re-identification with iterative soft clustering[J]. Knowledge-Based Systems, 2020: 106644. Link （中科院JCR 1区）
Zhongyang Xiong, Ke Qin*, Haobo Yang, Guangchun Luo. Learning Chinese Word Representation Better By Cascade Morphological N-gram, Neural Computing and Applications. 2020:1-12. Link. （中科院JCR 2区）
Hailin Wang, Ke Qin*, Guoming Lu, Guangchun Luo, Guisong Liu. Direction-sensitive relation extraction using Bi-SDP attention model. Knowledge-Based Systems, 2020, 198, 105928, 1-13. Link （中科院JCR 1区）
Jean-Paul Ainam，Ke Qin*, Guisong Liu, Guangchun Luo, Brighter Agyemang. Enforcing Affinity Feature Learning through Self-attention for Person Re-identification, ACM Transactions on Multimedia Computing, Communications, and Applications, 2020, 16(1). Link （中科院JCR 2区）
Ke Qin. On Chaotic Neural Network Design — A New Framework. Neural Processing Letters, 45(1):243-261, 2017.02. link
Guangchun Luo, Haifeng Sun, Ke Qin, Junbao Zhang. Greedy Zone Epidemic Routing in Urban VANETs. IEICE Transactions on Communications, 2015, E98-B(01): 219-230.
K. Qin, B. J. Oommen. Logistic neural networks: Their chaotic and pattern recognition properties. Neurocomputing, 125:184–194, 2014.02. link （中科院JCR 2区）
Y. C. Shi, P. Y. Zhu, Ke Qin. Projective synchronization of different chaotic neural networks with mixed time delays based on an integral sliding mode controller. Neurucomputing, 123:443–449, 2014. （中科院JCR 2区）
Y. Ma, S. Z. Zhu, Ke Qin. Combining the requirement information for software defect estimation in design time. Information Processing Letters, 114(9): 469-474, 2014.
Guangchun Luo, Junbao Zhang, Haojun Huang, Ke Qin, and Haifeng Sun. Exploiting Inter-contact Time for Routing in Delay Tolerant Networks. Transactions on Emerging Telecommunications Technologies, 2013, 24(6): 589-599.
G. C. Luo, J. S. Ren, K. Qin*. Dynamical associative memory: The properties of the new weighted chaotic adachi neural network. IEICE Transactions on Information and Systems, E95d(8):2158–2162, 2012. link
Guangchun Luo, Ying Ma, Ke Qin. Active Learning for Software Defect Prediction. IEICE Transactions on Information & Systems, 2012, E95-D(6):1680-1683.
Guangchun Luo, Junbao Zhang, Ke Qin, and Haifeng Sun. Location-Aware Social Routing in Delay Tolerant Networks. IEICE Transactions on Communications. 2012, E95-B(5), 1826-1829.
Guangchun Luo, Ying Ma, Ke Qin. Asymmetric Learning Based on Kernel Partial Least Squares for Software Defect Prediction. IEICE Transactions on Information and Systems, 2012, E95-D(7):2006-2008.
K. Qin, B. J. Oommen. Adachi-like chaotic neural networks requiring linear-time computations by enforcing a tree-shaped topology. IEEE Transactions on Neural Networks, 20(11):1797–1809, 2009. link （中科院JCR 1区）
Y. Ma, Ke Qin, S. Z. Zhu. Discrimination Analysis for Predicting Defect-Prone Software Modules. Journal of Applied Mathematics. http://dx.doi.org/10.1155/2014/675368, 2014.
Ying Ma, Ke Qin, Shunzhi Zhu. Discrimination Analysis for Predicting Defect-Prone Software Modules. Journal of Applied Mathematics, 2014, http://dx.doi.org/10.1155/2014/675368.
K. Qin, B. J. Oommen. Chaotic Neural Networks with a Random Topology Can Achieve Pattern Recognition. Chaotic Modeling and Simulation, 4:583-590, 2013 link
K. Qin, B. J. Oommen. Ideal chaotic pattern recognition is achievable: The ideal-m-adnn – its design and properties. Transactions on Computational Collective Intelligence XI, 8065:22–51, 2013. link
K. Qin, B. J. Oommen. The entire range of chaotic pattern recognition properties possessed by the Adachi neural network. Intelligent Decision Technologies, 6(1):27–41, 2012. link
K. Qin, B. J. Oommen. Ideal chaotic pattern recognition using the modified Adachi neural network. Chaotic Modeling and Simulation, 4:701–710, 2012. link
K. Qin, B. J. Oommen. An enhanced tree-shaped Adachi-like chaotic neural network requiring linear-time computations. Chaotic Systems: Theory and Applications, 284–293, 2010. link
K. Qin, B. J. Oommen. Chaotic Neural Networks with a “Small-World” Topology Can Achieve Pattern Recognition, Chaotic Modeling and Simulation, 4:379–386, 2014. link
J. S. Ren, K. Qin*, G. C. Luo. On Software Defect Prediction Using Machine Learning. Journal of Applied Mathematics. http://dx.doi.org/10.1155/2014/785435, 2014. link
Jean-Paul Ainam, K. Qin*, Guisong Liu, Guangchun Luo. Person Re-identification through Clustering and Partial Label Smoothing Regularization. In proceedings of the 2nd International Conference on Software Engineering and Information Management (ICSIM'19), 189-193, January 10–13, 2019, Bali, Indonesia. ACM, New York, USA.[ link](file:///H:/%E9%98%BF%E9%87%8C%E4%BA%91/%20https:/dl.acm.org/citation.cfm?id=3305205)
Jean-Paul Ainam, K. Qin*, Guisong Liu, Guangchun Luo. Deep Residual Network with Self Attention Improves Person Re-Identification Accuracy. In proceedings of the 2019 11th International Conference on Machine Learning and Computing (ICMLC'19), 380-385, February 22–24, 2019, Zhuhai, China. ACM, New York, USA. link
Haobo Yang, Zongyang Xiong, Jiexin Zhang, Ke Qin*, Guoming Lu, Cascade Morphological n-gram can Improve Chinese Words Representation Learning. In proceedings of the 2019 IEEE Green Computing and Communications (GreenCom'19), 842-847, July 14-17, 2019, Atlanta, USA.
K. Qin, B. J. Oommen. Chaotic Pattern Recognition Using the Adachi Neural Network Modified in a Small-World Way. In Proceedings of the 7th Chaotic Modeling and Simulation International Conference (Chaos2014), 391–398, Lisbon, Portugal, 2014
K. Qin, B. J. Oommen. Networking logistic neurons can yield chaotic and pattern recognition properties. In Proceedings of the IEEE International Conference on Computational Intelligence for Measure Systems and Applications(ICMSA2011), 134–139, Ottawa, Canada, 2011. link
K. Qin, B. J. Oommen. Chaotic and pattern recognition properties of a network of logistic neurons. In Proceedings of the 2nd International Conference on Computer Engineering and Technology (ICCET2010), vol.V3, 83–87, Chengdu, China, 2010. link
K. Qin, M. T. Zhou, Y. Feng. A novel multicast key exchange algorithm based on extended chebyshev map. In Proceedings of the 4th International Conference on Complex, Intelligent and Software Intensive Systems (CISIS2010), 643–648, Kracow, Poland, 2010. link
K. Qin, B. J. Oommen. Cryptanalysis of a Cryptographic Algorithm that Utilizes Chaotic Neural Networks. In Proceedings of the 29th International Symposium on Computer and Information Sciences (ISCIS2014), 167–174, Kracow, Poland, 2014. link
K. Qin, B. J. Oommen. Chaotic pattern recognition using the Adachi neural network modified in a random manner. In Proceedings of the 6th Chaotic Modeling and Simulation International Conference (Chaos2013)., Istanbul, Turkey, 2013.
K. Qin, B. J. Oommen. Chaotic pattern recognition: The spectrum of properties of the Adachi neural network. In Proceedings of the International Conference on Structural and Syntactic Pattern Recognition and Statistical Techniques in Pattern Recognition (SSSPR2008), Vol. 5342,540–550, Florida, USA, 2008. link
K. Qin, M. T. Zhou, N. Q. Liu, et al. A novel group key management based on Jacobian Elliptic Chebyshev Rational Map. In Proceedings of the IFIP International Conference Network and Parallel Computing(NPC2007), 287–295, Dalian, China 2007. link
部分已授权的专利（第一发明人）
一种基于上下文信息推理的生成式对话方法，专利号： ZL 2021 1 0975993.4, 授权时间：2023.10.13, 授权公告号：CN 113656569 B
一种基于深度学习的文本智能生成方法，专利号：ZL 2021 1 1331968.9， 授权时间：2023.05.12， 授权公告号：CN 113988274 B
一种基于深度学习辅助艺术绘画的方法，专利号：ZL 2019 1 0629814.4， 授权时间：2023.04.18， 授权公告号：CN 110322529 B
文本情感倾向的判别方法，专利号：ZL 2017 1 0812048.6， 授权时间：2020.11.03， 授权公告号：CN 107577665 B
一种基于词频的skip语言模型的训练方法，专利号：ZL 2016 1 0522055.8， 授权时间：2019.03.15， 授权公告号：CN 106257441 B
一种固定搭配型短语优先的两段式机器翻译方法，专利号： ZL 2016 1 0522056.2, 授权时间：2019.02.19， 授权公告号：CN 106156013 B
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电子科技大学
工学硕士学位
电子科技大学
工学博士学位
2020.8 -- 至今
电子科技大学 教授
2012.7 -- 2020.8
电子科技大学 副教授
2006.4 -- 2012.6
电子科技大学计算机学院 教师
Natural Language Processing
Machine Reasoning
Neural Networks
Data Science
