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个人履历
贾彩燕,博士,教授,博士生导师,交通数据分析与挖掘北京市重点实验室副主任,中国人工智能学会《粗糙集与软计算专业委员会》委员。2004年于中国科学院计算技术研究所获得计算机软件与理论专业博士学位,师从中国科学院院士陆汝钤研究员;2004年至2007年在复旦大学上海市智能信息处理实验室做博士后研究;2007年7月就职于北京交通大学计算机与信息技术学院,加入机器学习与数据挖掘研究团队。主要研究方向为:数据挖掘、社会计算、文本挖掘及生物信息学等。目前已在国际国内学术期刊和国际会议上发表论文50余篇。近年来主持国家自然科学基金面上项目两项,主持国家自然科学基金青年基金面上项目一项;参加国家自然科学基金重点项目一项,参加国家科技重大专项一项,参加北京市自然科学基金一项;获得湖南省科学技术进步二等奖一项,硕士论文获得湖南省百篇优秀硕士论文奖。
邮 箱:cyjia@bjtu.edu.cn
研究方向
主要研究方向机器学习、社会计算等。具体包括:社交短文本分析、基于深度学习的图像视频理解(如OCR及图像分类、语义标注等)、基于深度学习的自动问答、基于社交关系的推荐、网络社区发现等。
发表论文和著作
代表性论文:
近年来期刊论文:
[1] Zhineng Chen, Shanshan Ai, Caiyan Jia*, Structure-Aware Deep Learning for Product Image Classification, ACMTOMM, 2019. (SCI:2.019)
[2] Yafang Li, Caiyan Jia*, Xiangnan Kong, Liu Yang, and Jian Yu, Locally weighted fusion of structural and attribute information in graph clustering, IEEE trans. On Cybernetics, 2019. (SCI: 8.803)
[3] Yafang Li, Caiyan Jia*, Jianqiang Li, Xiaoyang Wang, Jian Yu, Enhanced semi-supervised community detection with action node and link selection. Physica A: Statistical Mechanics and its Applications, 2018, 510:219-232. (SCI:2.132)
[4] Zhenhai Chang, Xianjun Yin*, Caiyan Jia*, Xiaoyang Wang, Mixture models with entropy regularization for community detection in networks, Physica A: Statistical Mechanics and its Applications, 496:339-350, 2018. (SCI:2.132)
[5] Caiyan Jia, Matthew B. Carson, Xiaoyang Wang, Jian Yu, Concept Decompositions for Short Text Clustering by Identifying Word Communities, Pattern Recognition, Volume 76, pp. 691-703, April, 2018. (SCI:3.962)
[6] Caiyan Jia, Yanfang Li, Matthew B. Carson, Xiaoyang Wang, Jian Yu, Node Attribute-enhanced Community Detection in Complex Networks, Scientific Reports, 7:2626, Doi: 10.1038/s41598-017-02751-8, 2017. (SCI:4.122)
[7] Yafang Li, Caiyan Jia*, Jian Yu, A Parameter-free Community Detection Method Based on Centrality and Dispersion of Nodes in Complex Networks, Physica A: Statistical Mechanics and its Applications, 438: 454-468, 2015
[8] Baifang Chai, Caiyan Jia*, Jian Yu, An Online Expectation Maximiza[tion Algorithm for Exploring General Structure in Massive Networks, Physica A: Statistical Mechanics and its Applications, 438: 454-468, 2015
[9] Caiyan Jia*, M.B. Carson, Yang Wang et al., A New Exhaustive Method and Strategy for Finding Motifs in ChIP-enriched Regions, PLOS ONE, 9(1): e86044, 2014 (SCI, IF: 3.73)
[10] Caiyan Jia*, M.B. Carson, Jian Yu, A Fast Weak Motif Finding Algorithm Based on Community Detection in Graphs, BMC Bioinformatics, 14(227), pp. 1471-2150, 2013 (SCI, IF: 3.02)
[11] Bianfang Chai, Jian Yu*, Caiyan Jia*, et al., Combining a Polularity-productivity Stochastic Block with a Discriminative Content Model for Detecting General Structures. Physical Review E, 88(1):012807, , 2013 (SCI, IF: 2.313)
[12] Yanwen Jiang, Caiyan Jia*, Jian Yu, An Efficient Community Detection Algorithm by Greedy Surprise Maximization, Journal of Physics A: Mathematical and Theoretical, in press. (SCI, IF: 1.766)
[13] Yawen Jiang, Caiyan Jia*, Jian Yu, An Efficient Community Detection Method Based on Rank Centrality, Physica A: Statistical Mechanics and its Applications, doi:10.1016/j.physa.2012.12.013, 2013 (SCI, IF: 1.676)
[14] Caiyan Jia*, Ruqian Lu, Lusheng Chen, A Frequent Pattern Mining Method for Finding (l, d) Planted Motifs of Unknown Length in DNA sequences, International Journal of Computational Intelligence Systems, 4(5), pp. 1032-1041, 2011 (SCI, IF: 0.31)
[15] Zhipeng Hu*, Lusheng Chen, Caiyan Jia, Huanzhang Zhu, Wei Wang, Jiang Zhong, Screening of Potential Pseudo att Sites of Streptomyces Phage ΦC31 Integrase in the Human Genome. Acta Pharmacologica Sinica. 2013, 34(4), pp. 561-569, 2013 (SCI, IF: 2.354)
[16] 张雪松,贾彩燕,一种基于频繁词集表示的新文本聚类方法,计算机研究与发展,2108,55(1):102-112.
[17]李伟,贾彩燕,基于词共现网络的微博话题发珊方法,数字采集与处理,2018,第33(1):186-194.
[18]刘璐,贾彩燕,基于文本扩展模型的网络视频聚类方法,智能系统学报,2017(6):779-805.
[19]柴变芳, 贾彩燕, 于剑,基于概率模型的大规模网络结构发现方法,软件学报,第25卷,第12期,2753-2766页,2014.
[20]李亚芳,贾彩燕,于剑,一种新的社区/动态社区优化方法,数字采集与处理,第30卷,第6期,1215-1224页,2015.
[21]李亚芳,贾彩燕,于剑,应用非负矩阵分解模型的社区发现方法综述,计算机科学与探索,第10卷,第一期,1-13页,2016.
[22]温有福,贾彩燕,一种多模态融合的网络视频相关性度量方法,CCDM16,智能系统学报,2016, 11(3): 359-365.
[23]刘志雄,贾彩燕,面向用户兴趣与社区关系的微博话题检测方法,CCDM16,智能系统学报,2016, 11(3): 294-300.
[24]柴变芳, 于剑, 贾彩燕, 一种基于随机块模型的快速广义社区发现算法, 软件学报,第24卷,第11期,2699-2709页,2013
[25]姜雅文,贾彩燕,于剑,基于类原型的复杂网络重叠社区发现方法,模式识别与人工智能,第26卷,第7期,648-659页,2013
[26]柴变芳,赵晓鹏,贾彩燕,于剑,内容网络广义社区发现有效算法,计算机科学与探索,2014 ,8 (9): 1076-1084
[27]柴变芳,赵晓鹏,贾彩燕,于剑,大规模网络的三角形模体社区发现模型,南京大学学报,2014,50(4):466-473
[28]柴变芳,于剑,贾彩燕*,融合内容和链接的网络结构发现概率模型综述,小型微型计算机系统, 第34卷,第11期,2524-2528页,2013
[29]程飞,贾彩燕*,于剑,一种基于用户相似性的协同过滤推荐算法,计算机工程与科学,第35卷,第5期,161-165页,2013
[30] 康旭彬,贾彩燕*,一种改进的标签传播快速社区发现方法,合肥工业大学学报,第1期,43-47页,2013
近年来会议论文
[1] Chunyang Li, Caiyan Jia*, Zhineng Chen, Xiaoyan Gu and Hongyun Bao, psDirector: An Automatic Director for Watching View Generation from Panoramic Soccer Video, 25th International Conference on MultiMedia Modeling, Thessaloniki, Greece, Jan. 8-11, 2019
[2] Yafang Li, Xiangnan Kong, Caiyan Jia*, Janqian Li, Clustering Uncertain Graphs with Node attributes, Proceedings of machine learning research 95: 232-247, 2018, ACML 2018
[3] Sinan Zhu, Caiyan Jia, General Structure Preserving Network Embedding, 19th International Conference on Intelligent Data Engineering and Automated Learning – IDEAL 2018, Madrid, Spain, November 21–23, 2018, LNCS, volume 11314, pp 134-146
[4] Cuncun Shi, Caiyan Jia*, Zhineng Chen, FFDet: a Fully Convolutional Network for Coral Reef Fish Detection by Layer Fusion, IEEE International Conference on Visual Communications and Image Processing (VCIP 2018), Taichung, Taiwan, Dec. 9-12, 2018
[5] Yafang Li, Xiangnan Kong, Jianqiang Li, Caiyan Jia, Clustering uncertain graphs with node attributes, The 10th Asian conference on Machine learning, Beijing, Nov.11-14, 2018.
[6] Sinan Zhu, Caiyan Jia, General structure preserving network embedding, The 19th International Conference on Intelligent Data Engineering and Automated Learning, Nov. 21-23, 2018.
[7] Shanshan Ai, Caiyan Jia*, Zhenneng Chen, Large-Scale Product Classification via Spatial Attention based CNN Learning and Multi-Class Regression, MMM2017, 2017
[8] Yaoyao Qi, Caiyan Jia* Yafang Li, Community Detection Using Nonnegative Matrix Factorization with Orthogonal Constraint, Proceedings of the 8th internation conference on Anvanced Computational Intelligence, Chiang Mai, Thailand, Feb 14-16, 2016.
代表性著作:
科研项目及获奖情况
科研项目:
近年三年科研项目
1. 2019.1~2022.12,国家自然科学基金面上项目,批准号:61876016,主持,项目名称:动态属性图随机块模型及其应用
2. 2017.1~2021.12,国家自然科学基金重点项目,批准号:61632004,参加,项目名称:面向认知的多源学习理论和算法
3. 2017.1~2019.12,中央高校基本科研业务费专项资金,批准号,2017JBM023,主持,项目名称:属性图聚类若干关键问题研究
4. 2015.1~2018.12,国家自然科学基金面上项目,批准号:61473030,主持,项目名称:节点内容和链接相结合的大规模内容网络社区发现方法及应用研究
5. 2014.1~2015.12,数字出版国家重点实验室专项课题,主持,项目名称:学术论文的个性化推荐
......
获奖情况:
在学习和工作期间,曾获多项奖项。主要包括:
湖南省百篇优秀硕士论文奖(2003年)
湖南省科学技术进步二等奖(2006)
北京交通大学红果园双百人才D类计划(2011)
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