基本情况：

姓名：王悦

职称：副教授

系别：计算机科学与技术系

学术兼职：中国计算机学会（CCF）数据库专委会（NDBC）通讯委员。

联系方式：wangyuecs@cufe.edu.cn

主要工作兴趣为大规模数据的智能化分析及相关工业化项目的实施，有丰富的和企业合作研究的经验。目前的主要学术研究方向包括：自然语言领域的自动化分析、强化学习及链接预测等。近年在《IEEE Transaction on Knowledge and Data Engineering》，《 IEEE Transaction on Neural Networks Learning System》，《Pattern Recognition》，《World Wide Web Journal》,《Science China: Information Science》，《软件学报》，ICML, IJCAI, ICDM, IEEE Big Data, IEEE ICPR，WAIM等中国计算机学会推荐的国内外顶级期刊及会议发表论文数十篇。

教育背景：

2010年在四川大学计算机学院获得工学博士（导师：唐常杰）

工作经历：

2017.09-2018.09，伊利诺伊大学芝加哥分校（University of Illinois at Chicago），访问学者（合作导师：Philip S. Yu）

2014.10-至今，中央财经大学信息学院计算机科学与技术系，副教授

2012.06-2014.10，中央财经大学信息学院计算机科学与技术系，讲师

2010.07-2012.06，北京大学信息科学技术学院计算机科学与技术系，博士后

主要讲授课程：

(1)数据挖掘

(2) 数据库系统

(3)Java程序设计双语

代表性研究成果：

期刊论文

[1] Yue Wang, Yao Wan, Lu Bai, Lixin Cui, Zhuo Xu, Ming Li, Philip S. Yu, Edwin R. Hancock. Collaborative Knowledge Graph Fusion by Exploiting the Open Corpus. IEEE Trans. Knowl. Data Eng. 36(2): 475-489 (2024)（CCF A）

[2] Lixin Cui, Ming Li, Lu Bai, Yue Wang, Jing Li, Yanchao Wang, Zhao Li, Yunwen Chen, Edwin R. Hancock. QBER: Quantum-based Entropic Representations for un-attributed graphs. Pattern Recognit. 145: 109877 (2024) （CCF B）

[3] Lixin Cui, Lu Bai, Xiao Bai, Yue Wang, Edwin R. Hancock. Learning Aligned Vertex Convolutional Networks for Graph Classification. IEEE Trans. Neural Networks Learn. Syst. 35(4): 4423-4437 (2024) （CCF B）

[4] Lu Bai, Lixin Cui, Zhihong Zhang, Lixiang Xu, Yue Wang, Edwin R. Hancock.Entropic Dynamic Time Warping Kernels for Co-Evolving Financial Time Series Analysis. IEEE Trans. Neural Networks Learn. Syst. 34(4): 1808-1822 (2023) （CCF B）

[5] Lu Bai, Yuhang Jiao, Lixin Cui, Luca Rossi, Yue Wang, Philip S. Yu, Edwin R. Hancock. Learning Graph Convolutional Networks Based on Quantum Vertex Information Propagation. IEEE Trans. Knowl. Data Eng. 35(2): 1747-1760 (2023) （CCF A）

[6] Lixin Cui, Lu Bai, Yue Wang, Philip S. Yu, Edwin R. Hancock. Fused lasso for feature selection using structural information. Pattern Recognit. 119: 108058 (2021) （CCF B）

[7] Yue Wang, Chenwei Zhang, Shen Wang, Philip S. Yu, Lu Bai, Lixin Cui, Guandong Xu. Generative Temporal Link Prediction via Self-tokenized Sequence Modeling [J]. World Wide Web, 2020, 23: 2471-2488.（CCF B）

[8] Lixin Cui, Lu Bai, Zhihong Zhang, Yue Wang, Edwin R. Hancock. Identifying the most informative features using a structurally interacting elastic net. Neurocomputing （CCF C）336: 13-26 (2019)

[9] Fei Xiao, Yue Wang, Yinan Mei, Lu Bai, Lixin Cui. 基于出行模式子图的城市功能区域发现方法 (City Functional Region Discovery Algorithm Based on Travel Pattern Subgraph). 计算机科学 45(12): 268-278 (2018)

[10] 王悦, 黄威靖. ELPS: 一种高效的微博信息传播轨迹提取算法. 计算机科学, 2014, 41(4): 233-238, 255

[11] Yue Wang, Weijing Huang, Lang Zong, Tengjiao Wang, Dongqing Yang.Influence maximization with limit cost in social network [J]. Science China Information Sciences （CCF A）, 2013, 56(7): 1-14.

[12] 王悦, 唐常杰, 杨宁, 张悦, 李红军,郑皎凌.在不确定数据集上挖掘优化的概率干预策略.软件学报22.2 (2011).

[13] 王悦, 唐常杰, 杨宁, 陈瑜, 徐开阔. 基于基因表达式编程的进化模式定理. 四川大学学报(工程科学版) 41.2(2009).

[14] 杨宁, 唐常杰, 王悦, 陈瑜, 郑皎凌. 一种基于时态密度的倾斜分布数据流聚类算法. 软件学报21.5 (2010): 1031-1041.

[15] 杨宁, 唐常杰, 王悦, 陈瑜, 郑皎凌. 基于谱聚类的多数据流演化事件挖掘.软件学报21.10 (2010): 2395-2409.

[16] 李红军, 唐常杰, 乔少杰, 代术成, 王悦, 郑皎凌. UTR-Tree: 受限网络中移动对象不确定轨迹索引模型."四川大学学报: 工程科学版 (2010): 118-125.

学术会议

[1] Lu Bai, Lixin Cui, Ming Li, Yue Wang, Edwin R. Hancock. QBMK: Quantum-based Matching Kernels for Un-attributed Graphs. ICML 2024 (CCF A)

[2] Zhuo Xu, Yue Wang, Lu Bai, Lixin Cui, Guandong Xu. Extracting Financial Subdomain Documents via An Interpretable Writing Style Pattern[C]//2023 9th International Conference on Big Data and Information Analytics (BigDIA). IEEE, 2023: 684-691

[3] Lu Bai, Yuhang Jiao, Lixin Cui, Luca Rossi, Yue Wang, Philip S. Yu, Edwin R. Hancock. Learning Graph Convolutional Networks based on Quantum Vertex Information Propagation (Extended Abstract). ICDE 2022: 3132-3133 (CCF A)

[4] Wang Y, Xu Z, Bai L, et al. Cross-supervised joint-event-extraction with heterogeneous information networks[C]//2020 25th International Conference on Pattern Recognition (ICPR). IEEE, 2021: 278-285. （CCF C）

[5] Lu Bai, Lixin Cui, Yue Wang, Yuhang Jiao, Edwin R. Hancock. A Quantum-inspired Entropic Kernel for Multiple Financial Time Series Analysis. IJCAI 2020 （CCF A）.

[6] Yue Wang, Yao Wan, Chenwei Zhang, Lu Bai, Lixin Cui, Philip S. Yu. Competitive Multi-agent Deep Reinforcement Learning with Counterfactual Thinking. ICDM 2019 （CCF B）: 1366-1371

[7] Yue Wang, Chenwei Zhang, Shen Wang, Philip S. Yu, Lu Bai, Lixin Cui.Market Abnormality Period Detection via Co-movement Attention Model. IEEE BigData （CCF C） 2018: 1514-1523

[8] Yue Wang, Chenwei Zhang, Shen Wang, Philip S. Yu, Lu Bai, Lixin Cui.Deep Co-Investment Network Learning for Financial Assets. ICBK 2018: 41-48

[9] Lixin Cui, Lu Bai, Luca Rossi, Yue Wang, Yuhang Jiao, Edwin R. Hancock. A Deep Hybrid Graph Kernel Through Deep Learning Networks. ICPR （CCF C）2018: 1030-1035

[10] Yuhang Jiao, Lixin Cui, Lu Bai, Yue Wang. Analyzing Time Series from Chinese Financial Market Using a Linear-Time Graph Kernel. S+SSPR 2018: 227-236

[11] Yue Wang ，Lu Bai, Link prediction via Supervised Dynamic Network Formation, ICPR （CCF C）, 2016, Cancun, 2016.12.4-2016.12.8

[12] Wang Yue, Discovering the Causal Network of Terms from the Text Corpus, The 12th IEEE International Conference on e-Business Engineering (ICEBE) 2015, 2015.10.23-2015.10.25

[13] Yue, Wang. Exploring the Intervention Problem with the Networked Poisson Process in a Real Heterogeneous Social Network. Web-Age Information Management （CCF C）. Springer, 2014. 150-154.

[14] Yue Wang, Changjie Tang, Tengjiao Wang, Dongqing Yang, and Jun Zhu. Efficient Subject-oriented Evaluating and Mining Methods for Data with Schema Uncertainty. ADMA 2011.

[15] Yue Wang, Weijing Huang, Wei Chen, Tengjiao Wang, Dongqing Yang: Informed Prediction with Incremental Core-Based Friend Cycle Discovering. WAIM （CCF C）2011:530-541

[16] Yue Wang, Jie Zuo, Ning Yang, Lei Duan, Chang-an Yuan and Jun Zhu. An Efficient Approach for Mining Segment-Wise Intervention rules in Time-Series Streams. WAIM （CCF C）2010.

[17] Yue Wang, Changjie Tang, Chuan Li, Yu Chen, Ning Yang, Rong Tang. Intervention events detection and prediction in data streams. Advances in Data and Web Management （CCF C）.Springer Berlin Heidelberg,2009. 519-525.

[18] Wei Chen, Lang Zong, Weijing Huang, Gaoyan Ou, Yue Wang, Dongqing Yang.An Empirical Study of Massively Parallel Bayesian Networks Learning for Sentiment Extraction from Unstructured Text. APWeb （CCF C）2011 :424-435

[19] TengfeiJi, Xiaoyuan Bao, Yue Wang, Dongqing Yang. A Fuzzy K-modes-based Algorithm for Soft Subspace Clustering. Fuzzy Systems and Knowledge Discovery(FSKD), 2011 Eighth International Conference on. Vol. 2. IEEE, 2011.

[20] Hongjun Li, Changjie Tang, Shaojie Qiao,Yue Wang, Ning Yang, and Chuan Li, Hotspot District Trajectory Prediction.(Ed.H.T. Shen et al.) ): WAIM 2010 Workshops, LNCS 6185, pp. 74–84, 2010.©Springer-Verlag Berlin Heidelberg 2010

[21] Ning Yang, Changjie Tang, Yue Wang, Rong Tang, Chuan Li, Jiaoling Zheng, JunZhu, Mining Interventions from Parallel Event Sequences. In: Proc. of APWeb-WAIM （CCF C） 2009, P297-307.

[22] Jie Zuo, Changjie Tang, Lei Duan, Yue Wang, Liang Tang, Tianqing Zhang, and JunZhu. Meta Galaxy: A Flexible and Efficient Cube Model for Data Retrieval in OLAP. The International Workshop on Database and Information Retrieval &Aspects in Evaluating Holistic Quality of Ontology-based Information Retrieval (APWeb-WAIM Workshop), 2009.

[23] Yu Chen, Changjie Tang, Chuan Li, Yue Wang, Ning Yang, and Mingfang Zhu. HDN-GEP:A Novel Gene Expression Programming with High Density Node." Intelligent Computation Technology and Automation (ICICTA), 2008 International Conference on. Vol. 1. IEEE, 2008.

联系方式：wangyuecs@cufe.edu.cn