---------------------------------------------------------------------------------------------------------------------------------------------------------------------- 科研成果 近年来,研究组在贝叶斯优化、网络表示学习、图神经网络、社会化推荐系统、数据驱动的智能传染病防控、时空网络建模与挖掘等方面取得了多项创新性研究成果,主持或完成科技创新2030新一代人工智能重大项目,国家自然科学基金重点、面上、青年项目,军科委国防项目,华为校企联合等项目20多项,发表论文近200篇,其中在IEEE TPAMI、IEEE TKDE、IEEE TCYB、IEEE TNNLS、ACM TWEB、ACM TKDD、ML、JAAMAS、DKE、WWWJ、Information Sciences、AAAI、IJCAI、NeurIPS、ICLR、ACL、WWW、CIKM、ICDM、COLING、UbiComp等CCF A/B类期刊和会议上发表论文50余篇,国内一级学报论文20余篇,出版专著1部,译著1部,获国家发明专利10多项。项目组完成的项目组完成的“领域驱动的网络大数据分析理论与方法”获吉林省自然科学一等奖(2021),“大规模网络机器学习和数据挖掘方法”获吴文俊人工智能科学技术奖自然科学二等奖(2017),“复杂知识处理的基本方法研究”获吉林省自然科学二等奖(2014),“大数据和移动互联时代快速知识共享关键技术创新及应用”获中国商业联合会科学技术一等奖(2020)。 【相关论文】 图机器学习与图挖掘: [1] Bo Yang, Xueyan Liu, Yang Li, Xuehua Zhao. Stochastic blockmodeling and variational Bayes learning for signed network analysis,IEEE Transactions on Knowledge and Data Engineering (TKDE) , 2017, 29(9): 2026-2039.(CCF A) [2] Bo Yang, Xuehua Zhao. On the scalable learning of stochastic blockmodel. In Proceedings of the 29th AAAI Conference on Artificial Intelligence (AAAI’15), Jan 25-30, 2015:360-366. (CCF A) [3] Bo Yang, Xuehua Zhao, Xueyan Liu. Bayesian approach to modeling and detecting communities in signed network. The 29th AAAI Conference on Artificial Intelligence (AAAI’15), Jan 25-30, 2015: 1952-1958. (CCF A) [4] Bo Yang, Jiming Liu, Jianfeng Feng. On the spectral characterization and scalable mining of network communities.IEEE Transactions on Knowledge and Data Engineering(TKDE),2012,24(2):326-337.(CCF A) [5] Xueyan Liu, Bo Yang*, Hechang Chen, Katarzyna Musial, Hongxu Chen, Yang Li, Wangli Zuo. A Scalable Redefined Stochastic Blockmodel,ACM Transaction on Knowledge Discovery and Data Mining (TKDD), 2021, 15(3): 1-28. (CCF B) [6] Xueyan Liu, Bo Yang*, Wenzhuo Song,Katarzyna Musial, Wanli Zuo, Hongxu Chen, Hongzhi Yin. A block-based generative model for attributed network embedding.World Wide Web (WWWJ), 2021, 24(5): 1439-1464. (CCF B) [7] Bo Yang, Jiming Liu, Da-you Liu. Characterizing and extracting multiplex patterns in complex networks.IEEE Transactions on Systems, Man, and Cybernetics-Part B: Cybernetics (TCYB), 2012, 42(2):469-481. (CCF B) [8] Bo Yang, Di Jin, Jiming Liu, Dayou Liu. Hierarchical community detection with applications to real-world network analysis.Data & Knowledge Engineering (DKE), 2013, 83: 20-38. (CCF B) [9] Xueyan Liu, Wenzuo Song, Katarzyna Musial, Xuehua Zhao, Wanli Zuo, Bo Yang*, Semi-supervised stochastic blockmodel for structure analysis of signed networks,Knowledge-Based Systems(KBS), 2020, 195: 105714. (中科院1区) [10] Bo Yang, Hechang Chen, Xuehua Zhaoa, Masato Naka, Jing Huang. On characterizing and computing the diversity of hyperlinks for anti-spamming page ranking.Knowledge-Based Systems(KBS), 2015, 77: 56-67. (中科院1区) [11] Bo Yang, William K. Cheung, Jiming Liu. Community mining from signed social networks.IEEE Transactions on Knowledge and Data Engineering(TKDE), 2007, 19(10): 1333-1348. (CCF A) [12] Yang Li, Wenzhuo Song, Bo Yang*. Stochastic variational inference-based parallel and online supervise topic mode.Journal of Computer Science and Technology (JCST), 2018, 33(5): 1007-1022. (CCF B) [13] 赵学华,杨博*,陈贺昌.一种高效的随机块模型学习算法.软件学报, 2016, 27(9): 2248-2264. [14] 杨博,陈贺昌,朱冠宇,赵学华.基于超链接多样性分析的新型网页排名算法.计算机学报, 2014, 34(4): 833-847. [15] 刘大有,金弟,何东晓,杨建宁,黄晶,杨博*.复杂网络社区挖掘综述.计算机研究与发展, 2013, 50(10): 2140-2154 [16] 杨博,刘杰,刘大有,基于随机网络集成模型的广义网络社区挖掘算法.自动化学报,2012,38(5): 812-822.
复杂系统学习/流行病防控: [17] Hongbin Pei, Bo Yang*, Jiming Liu, Kevin Chang. Active Surveillance via Group Sparse Bayesian Learning.IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI),2022, 44(3): 1133-1148. (CCF A) ESI热点论文、高被引论文 [18] Hongbin Pei, Bo Yang*, Jiming Liu, Lei Dong. Group sparse Bayesian learning for actively surveillance on epidemic dynamics. In Proceedings of 32th AAAI Conference on Artificial Intelligence (AAAI’18), Feb 2-7, 2018.(CCF A) [19] Bo Yang, Hongbin Pei, Hechang Chen, Jiming Liu, Shang Xia. Characterizing and discovering spatiotemporal social contact patterns for healthcare.IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2017, 39(8), 1532-1546.(CCF A) [20] Yuan Bai, Bo Yang*, Zhanwei Du, Lauren Ancel Meyers. Location based surveillance for early detection of contagious outbreaks. In Procedings of the 2015 ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp’15), Sept 7-11, 2015: 77-80.(CCF A) [21] Bo Yang, Hua Guo, Yi Yang, Benyun Shi, Xiaonong Zhou, Jiming Liu. Modeling and mining spatiotemporal patterns of Infection risk from heterogeneous data for active surveillance planning. The 28th AAAI Conference on Artificial Intelligence (AAAI’14), Jul 27-31, 2014: 493-499. (CCF A) [22] Dayou Liu,Bo Yang*, Shang Gao,Yungang Zhu, Yong Lai. Intelligent CPSS and its application to health care computing,Science China (information sciences), 2016, 59(5): 050103:1-3.(CCF B) [23] Bo Yang, Hongbin Pei, Hechang Chen, Jiming Liu, Shang Xia. Modeling and mining spatiotemporal social contact of metapopulation from heterogeneous data. IEEE 14th International Conference on Data Mining (ICDM ’14), Dec 14-17, 2014: 630- 639. (CCF B) [24] 杨博,刘际明,杨建宁,白媛,刘大有.基于自治计算的流行病传播网络建模与推断.软件学报, 2012, 23(11): 2955-2970.
图神经网络、图优化和神经符号系统: [25] Hongbin Pei, Bingzhe Wei, Kevin Chang, Chunxu Zhang, Bo Yang*. Curvature Regularization to Prevent Distortion in Graph Embedding. The 34th International Conference on Neural Information Processing Systems (NeurPIS’20), Dec 6-12, 2020, 1-12. (CCF A) [26] Hongbin Pei, Bingzhe Wei, Kevin Chen-Chuan Chang, Yu Lei, Bo Yang*. Geom-GCN: geometric graph convolutional networks. In Proceedings of the 8th International Conference on Learning Representations (ICLR’20), Apr 26-30, 2020, 1-12. (清华A类论文) [27] Dongran Yu,Bo Yang*, Qianhao Wei, Anchen Li, Shirui Pan. A Probabilistic Graphical Model Based on Neural-Symbolic Reasoning for Visual Relationship Detection. Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. 2022: 10609-10618. (CCF A) [28] Jiaxu Cui, Bo Yang*, Bingyi Sun, Jiming Liu. Cost-aware Graph Generation: A Deep Bayesian Optimization Approach. The 35th AAAI Conference on Artificial Intelligence (AAAI’21), Feb 2-9, 2021,7142-7150. (CCF A) [29] Jiaxu Cui, Bo Yang*, Xia Hu. Deep Bayesian optimization on attributed graphs. In Proceedings of 33rd AAAI Conference on Artificial Intelligence (AAAI’19), Jan 27-Feb 1, 2019, 1377-1384.(CCF A) [30] Jiaxu Cui, Bo Yang*, Bingyi Sun, Xia Hu, Jiming Liu. Scalable and Parallel Deep Bayesian Optimization on Attributed Graphs,IEEE Transactions on Neural Networks and Learning Systems(TNNLS), 2022, 33(1): 103-116. (CCF B) [31] Jiaxu Cui, Qi Tan, Chunxu Zhang, Bo Yang*. A Novel Framework of Graph Bayesian Optimization and Its Applications to Real-World Network Analysis.Expert System with Applications, 2021, 170: 114524. (中科院1区) [32] 崔佳旭,杨博*.贝叶斯优化方法和应用综述.软件学报, 2018, 29(10):3068-3090 [33] 杨博,张钰雪晴,彭羿达,张春旭,黄晶.一种协同过滤式零次学习方法,软件学报,2021,32(9):2801-2815
智能推荐系统: [34] Anchen Li, Bo Yang, Huan Huo, Hongxu Chen, Guandong Xu, and Zhen Wang. Hyperbolic Neural Collaborative Recommender. IEEE Transactions on Knowledge and Data Engineering (TKDE), 2022. (Accepted) (CCF A) [35] Anchen Li, Bo Yang*, Huan Huo, Farookh Hussain. Hypercomplex Graph Collaborative Filtering. In Proceedings of the ACM Web Conference (WWW’22), Apr 25-29, 2022. (CCF A) [36] Bo Yang, Yu Lei, Jiming Liu, Wenjie Li. Social collaborative filtering by trust.IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2017, 39(8), 1633-1647. (CCF A) ESI高被引论文 [37] Bo Yang, Yu Lei, Dayou Liu, Jiming Liu. Social collaborative filtering by trust. The 23rd International Joint Conference on Artificial Intelligence (IJCAI’13), Aug 3-9, 2013: 2747-2753. (CCF A) [38] Anchen Li,Bo Yang*, Farookh Khadeer Hussain, Huan Huo. HSR: Hyperbolic Social Recommender,Information Sciences, 2022, 585: 275-288. (CCF B) [39] Anchen Li, Bo Yang*, Huan Huo, Farookh Khadeer Hussain. Leveraging Implicit Relations for Recommender Systems, Information Sciences, 2021, 579: 55-71. (CCF B) [40] Anchen Li, Bo Yang*. GSIRec: Learning with graph side information for recommendation, World Wide Web (WWWJ), 2021, 24(5): 1411-1437. (CCF-B) [41] Yuyao Liu, Bo Yang, Hongbin Pei, Huang Jing*. Neural Explainable Recommender Model Based on Attributes and Reviews. Journal of Computer Science and Technology (JCST), 2020, 35(6): 1446-1460. (CCF B)
【在研的科研项目】 [1] 复杂动态系统智能理论与方法研究,科技创新2030—“新一代人工智能”重大项目 [2] 领域驱动的新型属性图优化理论、方法及应用研究,国家自然科学基金区域创新发展联合基金重点支持项目 [3] 融合深度学习和贝叶斯优化的网络优化理论与方法,国家自然科学基金面上项目 [4] 面向大规模网络分析的贝叶斯随机块模型与算法研究,国家自然科学基金面上项目 |