学术论文: |
代表性论文如下:
[1]Yingji Li, Mengnan Du, Xin Wang, Mingchen Sun, Ying Wang(王英, 通讯作者). Mitigating Social Biases of Pre-trained Language Models via Contrastive Self-Debiasing with Double Data Augmentation[J]. Artificial Intelligence, 2024. (304永利集团官网入口C, CCF A类) [2]Rui Miao, Kaixiong Zhou, Yili Wang, Ninghao Liu, Ying Wang(王英), Xin Wang. Rethinking Independent Cross-Entropy Loss For Graph-Structured Data. ICML, 2024. (304永利集团官网入口D, CCF A类) [3]Yingji Li, Mengnan Du, Rui Song, Xin Wang, Ying Wang(王英). Data-Centric Explainable Debiasing for Improving Fairness in Pre-trained Language Models. In Proceedings of the Annual Meeting of the Association for Computational Linguistics(ACL) Findings, 2024. [4]Yingji Li, Mengnan Du, Xin Wang, Ying Wang(王英, 通讯作者). Prompt Tuning Pushes Farther, Contrastive Learning Pulls Closer: A Two-Stage Approach to Mitigate Social Biases[C]. In Proceedings of the Annual Meeting of the Association for Computational Linguistics(ACL), 2023.(304永利集团官网入口D, CCF A类) [5]Mingchen Sun, Kaixiong Zhou, Xin He, Ying Wang(王英, 通讯作者), Xin Wang. GPPT: Graph Pre-training and Prompt Tuning to Generalize Graph Neural Networks[C]. In Proceedings of the 28th Conference on Knowledge Discovery and Data Mining(KDD), 2022, pp1717-1727. (304永利集团官网入口D, CCF A类) [6]Bo Wang, Tao Shen, Guodong Long, Tianyi Zhou, Ying Wang(王英, 通讯作者). Structure-Augmented Text Representation Learning for Efficient Knowledge Graph Completion[C]. In Proceedings of the International World Wide Web Conference(WWW), 2021, pp1737-1748. (304永利集团官网入口D, CCF A类) [7]Xin Wang, Ying Wang(王英, 通讯作者), Yunzhi Ling. Attention Guide Walk Model in Heterogeneous Information Network for Multi-style Recommendation Explanation[C]. In Proceedings of the 34th AAAI Conference on Artificial Intelligence(AAAI), 2020, pp6275-6282. (304永利集团官网入口C, CCF A 类) [8]Yu Li, Ying Wang(王英, 通讯作者), Tingting Zhang, Jiawei Zhang, Yi Chang. Learning Network Embedding with Community Structural Information[C]. In Proceedings of the International Joint Conference on Artificial Intelligence(IJCAI), 2019, pp2937-2943. (304永利集团官网入口D, CCF A类) [9]Ying Wang(王英)#, Xin Wang, Jiliang Tang, WanliZuo. Modeling Status Theory in Trust Prediction[C]. In Proceedings of the 29th AAAI Conference on Artificial Intelligence(AAAI), 2015, Austin, Texas, USA, pp1875-1881, 2015.1.25-1.29. (304永利集团官网入口C, CCF A类) [10]Xin Wang, Ying Wang(王英), Wanli Zuo. Exploring Social Context for Topic Identification in Short and Noisy Text[C]. In Proceedings of the 29th AAAI Conference on Artificial Intelligence(AAAI), 2015, Austin, Texas, USA, pp1868-1874, 2015.1.25-1.29. (304永利集团官网入口C, CCF A类) [11]Zihao Chen. Ying Wang(王英, 通讯作者), Fuyuan Ma, Hao Yuan, Xin Wang. GPL-GNN: Graph Prompt Learning for Graph Neural Network[J]. Knowledge-Based Systems, 2024. (304永利集团官网入口D, 中科院一区) [12]Yili Wang, Kaixiong Zhou, Ninghao Liu, Ying Wang(王英), Xin Wang. Efficient Sharpness-Aware Minimization for Molecular Graph Transformer Models[C]. In Proceedings of the International Conference on Learning Representations (ICLR), 2024. (清华大学A) [13]Rui Miao, Yintao Yang, Yao Ma, Xin Juan, Haotian Xue, Jiliang Tang, Ying Wang(王英), Xin Wang. Negative Samples Selecting Strategy for Graph Contrastive Learning[J]. Information Sciences, 2022, 613: 667-681. (304永利集团官网入口D, 中科院一区) [14]Wajid Ali, Wanli Zuo, Wang Ying(王英), Rahman Ali, Gohar Rahman, Inam Ullah. Causality Extraction: A Comprehensive Survey and New Perspective[J]. Journal of King Saud University-Computer and Information Sciences, 2023, 35: 1-25. (304永利集团官网入口D, 中科院一区) [15]Xianglin Zuo, Wenqi Chen, Xianduo Song, Xin Wang, Ying Wang(王英, 通讯作者). Generating Real-world Hypergraphs via Deep Generative Models[J]. Information Sciences, 2023, 647(119412): 1-15. (304永利集团官网入口D, 中科院一区) [16]Ying Wang(王英)#, Yingji Li, Yue Wu, Xin Wang. Exploring Multiple Hypergraphs for Heterogeneous Graph Neural Networks[J]. Expert Systems With Applications, 2024, 236: 1-10. (304永利集团官网入口D, 中科院一区) [17]Yingji Li, Yue Wu, Mingchen Sun, Bo Yang, Ying Wang(王英, 通讯作者). Learning Continuous Dynamic Network Representation with Transformer-based Temporal Graph Neural Network[J]. Information Sciences, 2023.(304永利集团官网入口D, 中科院一区) [18]Mingchen Sun, Mengduo Yang, Yingji Li, Dongmei Mu, Xin Wang, Ying Wang(王英, 通讯作者). Structural-aware Motif-based Prompt Tuning for Graph Clustering[J]. Information Sciences, 2023. (304永利集团官网入口D, 中科院一区) [19]Xianglin Zuo, Hao Yuan, Bo Yang, Hongji Wang, Ying Wang(王英, 通讯作者). Exploring Graph Capsual Network and Graphormer for Graph Classification[J]. Information Sciences, 2023, 640: 1-17.(304永利集团官网入口D, 中科院一区) [20]Xianduo Song, Xin Wang, Yuyuan Song, Xianglin Zuo, Ying Wang(王英, 通讯作者). Hierarchical Recurrent Neural Networks for Graph Generation[J]. Information Sciences, 2022, 589: 250-264. (304永利集团官网入口D, 中科院一区) [21]Siyuan Guo, Ying Wang(王英,学生一作,导师二作), Hao Yuan, Zeyu Huang, Jianwei Chen, Xin Wang. TAERT: Triple-Attentional Explainable Recommendation with Temporal Convolutional Network[J]. Information Sciences, 2021, 567, pp185-200. (304永利集团官网入口D, 中科院一区) [22]Ying Wang(王英) #, Hongji Wang, Hui Jin, Xinrui Huang, Xin Wang. Exploring Graph Capsual Network for Graph Classification[J]. Information Sciences, 2021, 581, pp932-950. (304永利集团官网入口D, 中科院一区) [23]Yunzhi Ling, Ying Wang(王英, 通讯作者), Xin Wang, Yunhao Ling. Exploring Common and Label-Specific Features for Multi-Label Learning with Local Label Correlations, IEEE Access, 2020, 8: 50969-50982.(中科院二区) [24] Mengmeng Wang, Wanli Zuo, Xin Wang, Ying Wang(王英, 通讯作者). An Improved Density Peaks-based Clustering Method for Social Circle Discovery in Social Networks[J]. Neurocomputing, 2016, 179: 219-227. (中科院二区, CCF C类IF: 2.083) [25]Ying Wang(王英)#, Xin Wang, Wanli Zuo. Research on Trust Prediction from a Sociological Perspective[J]. Journal of Computer Science and Technology(JCST), 2015, 30(4): 843-858. (中科院三区,CCF B类, IF: 0.672) [26]Ying Wang(王英) #, Mingchen Sun, Hongji Wang, Yudong Sun. Research on Knowledge Graph Completion Model Combining Temporal Convolutional Network[J]. Mathematical Problems in Engineering, 2022, 1-13.(中科院三区) [27]Ying Wang(王英) #, Xin He, Hongji Wang, Yudong Sun, Xin Wang. Fast Explainable Recommendation Model by Combining Fine grained Sentiment in Review Data[J]. Computational Intelligence and Neuroscience, 2022, 1-18.(中科院三区) [28]Xianglin Zuo, Tianhao Jia, Xin He, Bo Yang, Ying Wang(王英, 通讯作者). Exploiting Dual-Attention Networks for Explainable Recommendation in Heterogeneous Information Networks[J]. Entropy, 2022, 24(1718): 1-19.(中科院三区) [29]Ying Wang(王英)#, Huilai Li, Wanli Zuo, Fengling He, Xin Wang, Kerui Chen. Research on Discovering Deep Web Entries. Computer Science and Information Systems, 2011.06, 8(3): 779-799. (中科院三区, IF:0.642) [30]Xin Wang, Ying Wang(王英, 通讯作者), Jianhua Guo. Building Trust Networks in the Absence of Trust Relations[J]. Frontiers of Information Technology & Electronic Engineering, 2017, 18(10): 1591-1600. (中科院三区, IF: 0.622) [31]Xin Wang, Ying Wang(王英, 通讯作者), Hongbin Sun. Exploring the Combination of Dempster-Shafer Theory and Neural Network for Predicting Trust and Distrust[J]. Computational Intelligence and Neuroscience, 2016, 5403105: 1-12. (中科院三区, IF:0.596) [32]Mengmeng Wang, Wanli Zuo, Ying Wang(王英, 通讯作者). A Multidimensional Nonnegative Matrix Factorization Model for Retweeting Behavior Prediction[J]. Mathematical Problems in Engineering, 2015, 936397: 1-10. (中科院四区, IF:1.082) [33]Mengmeng Wang, Wanli Zuo, Ying Wang(王英, 通讯作者). A Novel Adaptive Conditional Probability-based Predicting Model for User’s Personality Traits[J]. Mathematical Problems in Engineering, 2015, 472917: 1-14. (中科院四区, IF: 1.082) [34]Mengmeng Wang, Wanli Zuo, Ying Wang(王英, 通讯作者). A Multi-layer Naive Bayes Model for Analyzing User’s Retweeting Sentiment Tendency[J]. Computational Intelligence and Neuroscience, 2015, 510281: 1-11. (中科院四区, IF:0.596) [35]Fuyuan Ma, Wenqi Chen, Minhao Xiao, Xin Wang, Ying Wang(王英, 通讯作者). Explanation Chains Model Based on the Fine-Grained Data[C]. NLPCC 2019. (CCF C类会议) [36]沈鹏飞, 徐臻, 闫论, 王英(通讯作者). 基于嵌套生成对抗学习的网络嵌入[J]. 电子学报, 2022. (CCF中文A类) [37]吴越, 王英(通讯作者), 王鑫, 徐正祥, 李丽娜. 基于超图卷积的异质网络半监督节点分类[J]. 计算机学报, 2021, 44(11): 2248-2260. (CCF中文A类) [38]孙小婉, 王英(通讯作者), 王鑫, 孙玉东. 面向双注意力网络的特定方面情感分析模型[J]. 计算机研究与发展, 2019, pp2384-2395. (CCF中文A类) [39]王鑫, 王英(通讯作者), 左万利. 基于交互意见和地位理论的符号网络链接预测模型研究[J]. 计算机研究与发展, 2016(4): 764-775. (CCF中文A类) [40]王萌萌,左万利, 王英(通讯作者).基于加权非负矩阵分解的链接预测算法[J],电子学报,2016. (CCF中文A类) [41]王萌萌,左万利, 王英(通讯作者). 一种基于加权非负矩阵分解的多维用户人格特质识别算法[J], 计算机学报, 2016. (CCF中文A类) [42]王英#,王鑫,左万利. 基于社会学理论的信任关系预测模型研究[J]. 软件学报, 2014, 25(12): 2893-2904. [43]赵秋月,左万利,田中生,王英(通讯作者). 一种基于改进D-S证据理论的信任关系强度评估方法研究[J]. 计算机学报, 2014.04, 37(4): 873-883. (CCF中文A类) [44]王英#, 左祥麟, 左万利, 王鑫. 基于本体的Deep Web查询接口集成[J]. 计算机研究与发展, 2012.11, 49(11): 2383-2394. (CCF中文A类) ----------------------------------------------- 教研论文: [1]王英,王鑫,左万利. 操作系统课程改革的启发和思考,计算机教育,2017. -----------------------------------------------
申请发明专利10项: (1)王英, 孙小婉, 王鑫, 孙玉东, 于尤婧, 凌云志, 马涪元. 基于混合注意力网络的细粒度情感极性预测方法. 专利号: ZL 2019 1 0333298.0, 授权公告日: 2023.6.9. (2) 王英, 杨伟英, 王鑫, 左万利, 贾天浩, 郝琳琳. 基于超图卷积的超边链接预测方法. 专利号:ZL 2020 1 1276695.8,授权公告日:2022.7.1. (3) 王英, 贾天浩, 王鑫, 左万利, 杨伟英, 左祥麟. 一种融合异质信息网络的可解释推荐方法. 专利号:ZL 2020 1 1276253.3, 授权公告日:2022.9.16 (4)王英,孙玉东,王鑫,李畅,于尢婧,孙小婉,凌云志,马涪元. 面向细粒度情感的可解释推荐模型. 专利号:ZL 2019 1 0333302.3,授权公告日:2021.11.19. (5)王英,马涪元,王鑫,孙玉东,陈文祺,肖旻昊. 基于细粒度数据的可解释商品推荐方法. 专利号:ZL 201910333300.4,授权公告日:2021.9.24. (6)王英,左万利,王萌萌,王鑫, 彭涛. 基于最低阈值的用户个人品性多标记预测方法. 专利号:ZL 2014 1 0081840.5, 授权公告日: 2019.4.16. (7)王英,左万利,田中生,王鑫,彭涛,王萌萌,赵秋月. 基于前馈神经网络的可信与不可信用户识别方法,专利号:ZL 2013 1 0547349.2,授权公告日:2016.10.5. (8)左祥麟,杨博, 范利云, 左万利, 王俊华, 王英, 王泊, 郑慧中. 基于证据理论的网络质量评价方法.专利号:ZL 2016 1 0280055.1, 授权公告日:2018.5.15. (9)尚靖博,左祥麟,左万利,王英. 利用模糊理论对欺诈网页识别的方法,专利号:ZL 201611046454.8,授权公告日: 2018.9.5. (10)左万利,赫枫龄,王俊华,王鑫,凤丽洲,王英,彭涛,万海旭,苏雪阳,高宁宁,闫昭,张雪松. 基于本体的情境搜索方法,专利号:ZL 2012 1 0575284.8,授权公告日:2016.1.6. -----------------------------------------------
申请软件著作权4项: [1]基于机器学习的数据诊断系统V1.0, 2021
[2]大规模异质信息网络摘要可解释性研究平台V1.0, 2020 [3]政府政务新媒体校内评估可视化显示平台V1.0, 2020 [4]深度网搜索软件(V1.0), 2012.12, 中国, 登记号: 2013SR020480. |