* 表示通讯作者

【2024】

[1] Yuyan Wang, Jie Hu*, Fei Teng, Lianlan Peng, Shengdong Du, Tianrui Li, Knowledge-augmented and time-aware graph convolutional network for efficient traffic forecasting,Information Fusion(SCI，接收，中科院1区，人工智能top期刊)

[2] Juan Chen, Jie Hu*, Tianrui Li, Fei Teng, Shengdong Du, An effective relation-first detection model for relational triple extraction, Expert Systems with Applications, 2024, 238: 122007 (SCI，中科院1区，人工智能top期刊)

[3] Jianqiao Xiong; Mingwei Tang; Liansong Zong; Linxi Li; Jie Hu; Deng Bian; Shixuan Lv, INA-Net: An integrated noise-adaptive attention neural network for enhanced medical image segmentation, Expert Systems with Applications, 2024-12 DOI: 10.1016/j.eswa.2024.125078

[4] Jie Hu*, Chenghao Yang, Kai Huang, Hongjun Wang, Bo Peng, and Tianrui Li. Information Bottleneck Fusion for Deep Multi-View Clustering. Knowledge-Based Systems 289 (2024)(SCI, 中科院1区，计算机科学top期刊)

[5] Fei Teng, Quanmei Zhang, Xiaomin Zhou, Jie Hu, Tianrui Li, Few-shot ICD coding with knowledge transfer and evidence representation, Expert Systems with Applications, 2024, 238: 121861(SCI，中科院1区，人工智能top期刊)

【2023】

[1] Bassoma Diallo, Jie Hu*, Tianrui Li, Ghufran Ahmad Khan, Xinyan Liang, Hongjun Wang, Auto-attention Mechanism for Multi-view Deep Embedding Clustering, Pattern Recognition, Volume 143, November 2023, https://doi.org/10.1016/j.patcog.2023.109764 (SCI,中科院1区，计算机科学top期刊)

[2] Ghufran Ahmad Khan, Jie Hu*, Tianrui, Li, Diallo Bassoma, Shengdong Du. Multi-view clustering for multiple manifold learning via concept factorization, Digital Signal Processing, v140, 2023，https://doi.org/10.1016/j.dsp.2023.104118（SCI）

[3] Ghufran Ahmad Khan, Jie Hu*, Tianrui Li, Bassoma Diallo, Shengdong Du, Multi-view subspace clustering for learning joint representation via low-rank sparse representation, Applied Intelligence，53, 22511–22530 (2023). https://doi.org/10.1007/s10489-023-04716-z (SCI, 中科院2区，计算机：人工智能领域期刊)

[4] Lishan Wu, Jie Hu*, Fei Teng, Tianrui Li, Shengdong Du, Text semantic matching with an enhanced sample building method based on contrastive learning. International Journal of Machine Learning and Cybernetics, v 14, n 9, p 3105-3112, 2023 (SCI)

[5] Jiabin Tang, Lianghao Xia, Jie Hu and Chao Huang, Spatial-Temporal-Aware Meta Graph Contrastive Learning, In: 32nd ACM International Conference on Information and Knowledge Management (CIKM), UK, 21 - 25 October 2023, 已接收 (CCF B类会议)

【2022】

Tianrui Li, Rui Mao, Guoyin Wang, Fei Teng, Lei Zhang, Li Wang, Laizhong Cui, Jie Hu (Eds.),Big Data, 10th CCF Conference, BigData 2022, Chengdu, China, November 18–20, 2022, Proceedings, Part of the book series: Communications in Computer and Information Science (CCIS, volume 1709)https://doi.org/10.1007/978-981-19-8331-3（主编CCF学术会议论文集，EI）

[1] Huifa Liao, Jie Hu*, Tianrui Li, Shengdong Du, Bo Peng, Deep linear graph attention model for attributed graph clustering, Knowledge-Based Systems, v 246, June 21, 2022 (SCI, 中科院1区，计算机：人工智能领域top期刊)

[2]Chenbing Li, Jie Hu*, Tianrui Li, Shengdong Du, Fei Teng, An effective multi-task learning model for end-to-end emotion-cause pair extraction, Applied Intelligence, v 53, n 3, p 3519-3529, February 2023.(SCI, 中科院2区，计算机：人工智能领域期刊)

[3]Dan Huang, Jie Hu*, Tianrui Li, Shengdong Du, Hongmei Chen, Consistency regularization for deep semi-supervised clustering with pairwise constraints, International Journal of Machine Learning and Cybernetics,v 13, n 11, p 3359-3372, November 2022.(SCI)

[4]Wenwen Liu, Jie Hu*, Shengdong Du, Hongmei Chen, Fei Teng, A method of sharing sentence vectors for opinion triplet extraction, Neural Processing Letters, v 55, n 1, p 751-772, February 2023 (SCI)

[5]Xiaohui Chen, Jie Hu*, Shengdong Du, and Fei Teng. Entity Alignment between Knowledge Graphs via Contrastive Learning. In Machine Learning, Multi Agent and Cyber Physical Systems. World Scientific Proceedings Series on Computer Engineering and Information Science, 209-17: WORLD SCIENTIFIC, 2022.

[6]张熠玲,杨燕*,周威,欧阳小草,胡节,CMvSC:知识迁移下的深度一致性多视图谱聚类网络,软件学报, 2022,33(04)(一级学报，北大核心)

[7]Jiabin Tang, Tang Qian, Shijing Liu, Shengdong Du∗,Jie Hu, Tianrui Li, Spatio-Temporal Latent Graph Structure Learning for Traffic Forecasting, In: International Joint Conference on Neural Networks (IJCNN), Padua, Italy, 2022, pp. 1-8, doi: 10.1109/IJCNN55064.2022.9892191.(CCF C类会议)

【2021】

Shuwei Chen, Jie Hu, Tianrui Li, Luis Martínez, Jun Liu: 16th International Conference on Intelligent Systems and Knowledge Engineering, ISKE 2021, Chengdu, China, November 26-28, 2021. IEEE 2021, ISBN 978-1-6654-0553-9 （主编国际会议论文集，EI）

[1] Shuai Chang, Jie Hu*, Tianrui Li, Hao Wang, and Bo Peng, Multi-view clustering via deep concept factorization, Knowledge-Based Systems,v 217, April 6, 2021 (SCI，中科院1区，计算机：人工智能领域top期刊)

[2] Bassoma Diallo, Jie Hu*, Tianrui Li, Ghufran Ahmad Khan, Xinyan Liang, and Yimiao Zhao, Deep embedding clustering based on contractive autoencoder, Neurocomputing, v 433, p 96-107, April 14, 2021 (SCI, 中科院2区，计算机：人工智能领域top期刊)

[3] Ghufran Ahmad Khan, Jie Hu*, Tianrui Li, Bassoma Diallo, and Yimiao Zhao, Multi-view low rank sparse representation method for three-way clustering, International Journal of Machine Learning and Cybernetic, v 13, n 1, p 233-253, January 2022 (SCI, 中科院2区)

[4] Bassoma Diallo, Jie Hu*, Tianrui Li, Ghufran Ahmad Khan, and Ahmed Saad Hussein,Multi-view document clustering based on geometrical similarity measurement,International Journal of Machine Learning and Cybernetics, v 13, n 1, p 233-253, January 2022 (SCI,中科院2区)

[5] Ghufran Ahmad Khan, Jie Hu*, Tianrui Li, Bassoma Diallo, and Hongjun Wang, Multi-view data clustering via non-negative matrix factorization with manifold regularization, International Journal of Machine Learning and Cybernetics, v 13, n 3, p 677-689, March 2022 (SCI, 中科院2区)

[6] Jie Hu*, Yi Pan, Tianrui Li, and Yan Yang, TW-Co-MFC: Two-level weighted collaborative fuzzy clustering based on maximum entropy for multi-view data, Tsinghua Science and Technology, vol. 26, no. 2, pp. 185-198, 2021. (SCI, 中科院3区)

[7] Weiting Xu, Jie Hu*, Shengdong Du, Yan Yang, K-Means Clustering with Fairness Constraints, In: Proceedings of the 16th International Conference on Intelligent Systems and Knowledge Engineering (ISKE), pp.215-222, 2021.(EI)

【2020】

[1] Shanwen Yang, Tianrui Li, Xun Gong, Bo Peng, and Jie Hu, A review on crowd simulation and modeling, Graphical Models, vol. 111, 2020.

[2] Shu Wang, Tianrui Li, Chuan Luo, Jie Hu, Hamido Fujita, and Tianqiang Huang, A novel approach for efficient updating approximations in dynamic ordered information systems, Information Sciences, vol. 507, pp. 197-219, 2020.

【2019】

[1] Xueli Xiao, Thosini Bamunu Mudiyanselage, Chunyan Ji, Jie Hu, and Yi Pan, Fast deep learning training through intelligently freezing layers, in 5th IEEE International Conference on Smart Data, iThings/GreenCom/CPSCom/SmartData 2019, July 14, 2019 - July 17, 2019, Atlanta, GA, United states, 2019, pp. 1225-1232: Institute of Electrical and Electronics Engineers Inc.

[2] Vinath Mekthanavanh, Tianrui Li, Hua Meng, Yan Yang, and Jie Hu, Social web video clustering based on multi-view clustering via nonnegative matrix factorization, International Journal of Machine Learning and Cybernetics, vol. 10, no. 10, pp. 2779-2790, 2019.

[3] Vinath Mekthanavanh, Tianrui Li, Jie Hu, and Yan Yang, Social web video clustering based on multi-modal and clustering ensemble, Neurocomputing, vol. 366, pp. 234-247, 2019.

[4] Jing Li, Yan Yang, and Jie Hu, Multi-Objective Particle Swarm optimization Algorithm Based on Angle Preference and Three-Archive Sets, in 14th IEEE International Conference on Intelligent Systems and Knowledge Engineering, ISKE 2019, November 14, 2019 - November 16, 2019, Dalian, China, 2019, pp. 630-636: Institute of Electrical and Electronics Engineers Inc.

[5] Ghufran Ahmad Khan, Jie Hu*, Tianrui Li, Bassoma Diallo, and Qianqian Huang, Weighted Multi-View Data Clustering via Joint Non-Negative Matrix Factorization, in 14th IEEE International Conference on Intelligent Systems and Knowledge Engineering, ISKE 2019, November 14, 2019 - November 16, 2019, Dalian, China, 2019, pp. 1159-1165: Institute of Electrical and Electronics Engineers Inc.

[6] Qianqian Huang, Tianrui Li, Xin Yang, and Jie Hu, Dynamical Information Fusion of Multisource Incomplete Hybrid Information Systems Based on Conditional Entropy, in 14th IEEE International Conference on Intelligent Systems and Knowledge Engineering, ISKE 2019, November 14, 2019 - November 16, 2019, Dalian, China, 2019, pp. 1-8: Institute of Electrical and Electronics Engineers Inc.

[7] Jie Hu*, Yi Pan, Tianrui Li, and Yan Yang, TW-Co-MFC: Two-level weighted collaborative multi-view fuzzy clustering based on maximum entropy, in 7th International Conference on Advanced Cloud and Big Data, CBD 2019, September 21, 2019 - September 22, 2019, Suzhou, China, 2019, pp. 303-308: Institute of Electrical and Electronics Engineers Inc.

[8]Jie Hu*, Tianrui Li, Yan Yang, Peng Xie, and Xueli Xiao, RFMC: A Rough Fuzzy Multi-view Clustering Approach, in 14th IEEE International Conference on Intelligent Systems and Knowledge Engineering, ISKE 2019, November 14, 2019 - November 16, 2019, Dalian, China, 2019, pp. 142-147: Institute of Electrical and Electronics Engineers Inc.

[9] Bassoma Diallo, Jie Hu*, Tianrui Li, Ghufran Khan, and Chunyan Ji, Concept-Enhanced Multi-view Clustering of Document Data, in 14th IEEE International Conference on Intelligent Systems and Knowledge Engineering, ISKE 2019, November 14, 2019 - November 16, 2019, Dalian, China, 2019, pp. 1258-1264: Institute of Electrical and Electronics Engineers Inc.

[10] Muqeet Ahmad, Jie Hu*, Mushtaq Ahmad, Huda Zaid Ul, and Faisal Khurshid, Optimal Cluster Leader Selection Using MCDM Methods in MWSN: A Comparative Study, in 14th IEEE International Conference on Intelligent Systems and Knowledge Engineering, ISKE 2019, November 14, 2019 - November 16, 2019, Dalian, China, 2019, pp. 240-247: Institute of Electrical and Electronics Engineers Inc.

【2018】

[1] Vinath Mekthanavanh, Tianrui Li, Jie Hu, and Yan Yang, Web video clustering based on emotion category, in 2018 International Conference on Big Data Engineering and Technology, BDET 2018, August 25, 2018 - August 27, 2018, Chengdu, China, 2018, pp. 87-91: Association for Computing Machinery.

【2017】

[1] Anping Zeng, Tianrui Li, Jie Hu, Hongmei Chen, and Chuan Luo, Dynamical updating fuzzy rough approximations for hybrid data under the variation of attribute values, Information Sciences, vol. 378, pp. 363-388, 2017.

[2] Yingge Xu, Yan Yang, Hongjun Wang, and Jie Hu, An overlapping clustering approach with correlation weight, in International Joint Conference on Rough Sets, IJCRS 2017, July 3, 2017 - July 7, 2017, Olsztyn, Poland, 2017, vol. 10313 LNAI, pp. 611-619: Springer Verlag.

[3] Jie Hu, Tianrui Li, Chuan Luo, Hamido Fujita, and Yan Yang, Incremental fuzzy cluster ensemble learning based on rough set theory, Knowledge-Based Systems, vol. 132, pp. 144-155, 2017.

[4] Jie Hu, Tianrui Li, Chuan Luo, Hamido Fujita, and Shaoyong Li, Incremental fuzzy probabilistic rough sets over two universes, International Journal of Approximate Reasoning, vol. 81, pp. 28-48, 2017.

【2016】

[1] Mingwei Tang, Shenke Zeng, Xiaoliang Chen, Jie Hu, and Yajun Du, An adaptive image steganography using AMBTC compression and interpolation technique, Optik, vol. 127, no. 1, pp. 471-477, 2016.

[2] Jie Hu, Tianrui Li, Hongjun Wang, and Hamido Fujita, Hierarchical cluster ensemble model based on knowledge granulation, Knowledge-Based Systems, vol. 91, pp. 179-188, 2016.

【2015】

[1] Anping Zeng, Tianrui Li, Chuan Luo, and Jie Hu, Incremental updating fuzzy rough approximations for dynamic hybrid data under the variation of attribute values, in 14th International Conference on Machine Learning and Cybernetics, ICMLC 2015, July 12, 2015 - July 15, 2015, Guangzhou, China, 2015, vol. 1, pp. 157-162: IEEE Computer Society.

[2] Mingwei Tang, Wen Song, Xiaoliang Chen, and Jie Hu, An image information hiding using adaptation and radix, Optik, vol. 126, no. 23, pp. 4136-4141, 2015.

[3] Mingwei Tang, Jie Hu, Wen Song, and Shengke Zeng, Reversible and adaptive image steganographic method, AEU - International Journal of Electronics and Communications, vol. 69, no. 12, pp. 1745-1754, 2015.

[4] Shaoyong Li, Tianrui Li, and Jie Hu, Update of approximations in composite information systems, Knowledge-Based Systems, vol. 83, no. 1, pp. 138-148, 2015.

[5] Jie Hu, Tianrui Li, Chuan Luo, and Shaoyong Li, Incremental fuzzy probabilistic rough sets over dual universes, in IEEE International Conference on Fuzzy Systems, FUZZ-IEEE 2015, August 2, 2015 - August 5, 2015, Istanbul, Turkey, 2015, vol. 2015-November: Institute of Electrical and Electronics Engineers Inc.

[6] Jie Hu, Tianrui Li, Hongmei Chen, and Anping Zeng, An incremental learning approach for updating approximations in rough set model over dual universes, International Journal of Intelligent Systems，vol. 30, pp. 923-947,2015.

[7] Jie Hu and Tianrui Li, Reversible steganography using extended image interpolation technique, Computers and Electrical Engineering, vol. 46, pp. 447-455, 2015.

[8] Hongmei Chen, Tianrui Li, Chuan Luo, and Jie Hu, Dominance-based neighborhood rough sets and its attribute reduction, in 10th International Conference on Rough Sets and Knowledge Technology, RSKT 2015, November 20, 2015 - November 23, 2015, Tianjin, China, 2015, vol. 9436, pp. 89-99: Springer Verlag.

【2013】

[1] Mingwei Tang, Jie Hu, and Wen Song, A high embedding efficiency speech information hiding approach, in WIT Transactions on Information and Communication Technologies, May 7, 2013 - May 8, 2013, Wuhan, China, 2014, vol. 46 VOLUME 1, pp. 847-854: WITPress.

[2] Mingwei Tang, Jie Hu, and Wen Song, A high capacity image steganography using multi-layer embedding, Optik, vol. 125, no. 15, pp. 3972-3976, 2014.

[3] Jie Hu, Tianrui Li, and Anping Zeng, An incremental learning approach for updating approximations in rough set model over dual-universes, in 8th International Conference on Intelligent Systems and Knowledge Engineering, ISKE 2013, November 20, 2013 - November 23, 2013, Shenzhen, China, 2014, vol. 278, pp. 43-51: Springer Verlag.

[4] Jie Hu, Tianrui Li, and Anping Zeng, An Incremental Learning Approach for Updating Approximations in Rough Set Model Over Dual-Universes, in Knowledge Engineering and Management - Proceedings of the 8th International Conference on Intelligent Systems and Knowledge Engineering, ISKE 2013, 2014, vol. 278, pp. 43-51: Springer Verlag.

[5] Mingwei Tang, Jie Hu, Mingyu Fan, and Wen Song, A steganalysis by adjacency pixel bits structure, Computers and Electrical Engineering, vol. 39, no. 2, pp. 488-496, 2013.

[6] Mingwei Tang, Wen Song, and Jie Hu, Analysis and modeling of the elevator system based on colored cyber net, in 2009 WRI World Congress on Software Engineering, WCSE 2009, May 19, 2009 - May 21, 2009, Xiamen, China, 2009, vol. 3, pp. 167-170: IEEE Computer Society.