中国科学院计算技术研究所何清男博导__中科大考研真题_中科院考研真题

研究领域

机器学习、大数据挖掘等人工智能领域

招生信息

招生专业

081202-计算机软件与理论
081203-计算机应用技术
083500-软件工程

招生方向

机器学习、数据挖掘、人工智能
计算机技术
软件工程

教育背景

1997-09--2000-07 北京师范大学博士

学历

1997年8月-2000年7月北京师范大学模糊数学与人工智能专业博士毕业，获博士学位

学位

北京师范大学 19970801--20000730 博士
郑州大学 19850801--19870730硕士
河北师范大学 19810801--19850730学士

出国学习工作

2001年11月俄罗斯圣彼得堡信息与自动化研究所合作交流,执行中俄政府间科技合作项目

2003年10月澳大利亚UniSA高级访问学者，执行中澳国际特别基金合作项目
2004年10月澳大利亚UTS, 中国科学院高级访问学者计划.

工作经历

        2000年8月北京师范大学博士毕业后，进入中国科学院计算技术研究所做博士后工作，出站后留所工作，现任中国科学院计算技术研究所研究员、博士生导师，中国科学院智能信息处理重点实验室机器学习与数据挖掘课题组负责人。兼任中国人工智能学会副秘书长，常务理事，机器学习专业委员会常务理事, 分布智能与知识工程专业委员会秘书长，中国电子学会云计算专家委员会和大数据专家委员会委员。
        主要研究领域：机器学习与数据挖掘，基于云计算的大数据挖掘。主要学术贡献：提出了基于超曲面的覆盖学习算法；提出极小样本集抽样方法与相关理论；提出了基于进化规划的基于摄动的模糊聚类改进算法，解决了模糊聚类失真问题；证明了模糊集扩展原理在范畴论意义下的合理性；提出概念语义空间用于知识管理；提出基于极限学习机的分类、聚类、回归、异常发现算法。在国内外重要刊物和会议上发表近百篇学术论文，40多篇文章发表在SCI国际期刊，被EI收录66篇。
        在云计算和大数据挖掘应用方面，2008年底，何清带领他的中科院计算所机器学习与数据挖掘团队，受中国移动研究院委托开发完成了基于云计算的并行数据挖掘平台，用于TB级实际数据的挖掘，实现了高性能、低成本的数据挖掘，通过这次创新，使我国获得了自主知识产权的基于云计算的数据挖掘技术。受大会邀请在第二、三、六届中国云计算大会上作了技术报告。何清先后主持完成多个有关数据挖掘的国家自然科学基金项目和863项目，承担完成或参加完成的多项国家自然科学基金项目被评为优或特优。承担完成了两项863项目获得好评。提出了一系列有效的数据挖掘算法和多个并行机器学习算法。组织开发实现了四十多个并行机器学习算法，所开发的多个数据挖掘软件获得了软件著作权，并实际应用到电信、电力、信息安全、环保、保险行业的数十家企业，为企业带来了可观的经济效益和社会效益。2015年大数据挖掘算法与云服务科研成果获得吴文俊人工智能创新奖。

工作简历

2008-10~现在, 中国科学院计算技术研究所, 研究员
2007-06~现在, 中国科学院计算技术研究所, 博士生导师
2006-05~现在, 中国科学院研究生院, 教授
2002-10~2007-09,中国科学院计算技术研究所, 硕士生导师
2002-08~2008-09,中国科学院计算技术研究所, 副研究员
2000-08~2002-07,中国科学院计算技术研究所, 博士后

社会兼职

2018-05-12-今,中国人工智能学会知识工程与分布智能专业委员会, 副主任委员
2014-04-25-今,中国电子学会大数据专家委员会, 委员
2012-05-31-今,中国通信学会大数据专家委员会, 委员
2009-06-01-今,中国电子学会云计算专家委员会, 委员
2003-08-01-今,中国人工智能学会, 副秘书长

教授课程

认知计算
人工智能基础
云计算与大数据管理系列讲座
模糊数学及计算机应用

专利与软著

发明专利

（ 1 ）一种采用决策树的数据分类方法和系统, 发明, 2011, 第 2 作者, 专利号: 201110143821.7

（ 2 ）一种确定数据样本类别的方法及其系统 , 发明, 2010, 第 1 作者, 专利号: 200910077994.6

（ 3 ）一种关联规则挖掘方法及其系统 , 发明, 2010, 第 1 作者, 专利号: 200910077996.5

（ 4 ）一种数据挖掘系统中数据聚类的方法、系统及装置, 发明, 2011, 第 1 作者, 专利号: 201010102976.1

（ 5 ）数据关联规则挖掘实现方法与系统, 发明, 2011, 第 1 作者, 专利号: 200910091865.2

（ 6 ）聚类实现方法及系统 , 发明, 2011, 第 1 作者, 专利号: 200910091864.8

（ 7 ）聚类实现方法及系统, 发明, 2011, 第 1 作者, 专利号: 200910091866.7

（ 8 ）一种基于MapReduce的分布式垂直交叉网络爬虫系统, 发明, 2013, 第 2 作者, 专利号: 201310146080.7

（ 9 ）一种用于大数据的基于超曲面的分类方法及系统, 发明, 2013, 第 1 作者, 专利号: 201310926826.2，

（ 10 ）一种面向大数据的分布式主题发现方法及系统, 发明, 2013, 第 2 作者, 专利号: 201310526790.2

（ 11 ）描述型多维度复杂事件序列的并行频繁情节挖掘方法与系统, 发明, 2017, 第 5 作者, 专利号: 201610524750.8

（ 12 ）基于Spark的高效并行自动编码机及系统, 发明, 2016, 第 5 作者, 专利号: 2016101470075

（ 13 ）一种用于大数据的并行半定义分类方法与系统, 发明, 2016, 第 5 作者, 专利号: 201610570978.0

（１４）一种多标记学习方法，发明，２０１８，第 5 作者，申请号：201810062864.4

软件著作权

1.Web挖掘云服务平台[简称WMCS]V1.0，中国2013SR027808

2.基于云计算的Web 挖掘系统[简称CWMS]V1.0，中国2012SR119823

3.数据挖掘云服务平台[简称COMS]V1.0，中国 2010SR060647

4.并行分布式数据挖掘软件系统[简称PDMiner]V1.0，中国 2010SR005800

5.迁移学习系统[简称TLS] V1.0，中国 2015SR195765

6.城市人口全生命周期数据挖掘系统[简称UWDMS]V1.0，中国 2015SR071535

7.基于几何超曲面的分类系统[简称HSC]V1.0，中国 2008SR02159

8.Web 智能信息处理软件[简称GHunt] V2.0，中国 2008SR35473

9.Web 智能信息处理软件[简称GHunt] V1.0，中国 2004SR07403

10.多策略数据挖掘平台[简称MSMiner] V1.0，中国 2003SR6886

11.潜在离网用户预测系统POSUPS V1.0，中国 2018SR045680

奖励信息

（1）吴文俊人工智能科学技术创新奖——大数据挖掘算法与云服务, 二等奖, 省级, 2015
（2）北京市科学技术奖——主体网格智能平台, 三等奖, 省级, 2006

合作情况

项目协作单位

美国Rutgers, the State University of New Jersey
俄罗斯圣彼得堡信息与自动化研究所
澳大利亚悉尼技术大学
中国移动通信有限公司研究院

指导学生

已指导学生

赵秀荣硕士研究生 081202-计算机软件与理论

谭庆博士研究生 081202-计算机软件与理论

庄福振博士研究生 081202-计算机软件与理论

赵卫中博士研究生 081202-计算机软件与理论

李金成硕士研究生 081202-计算机软件与理论

马旭东硕士研究生 081202-计算机软件与理论

李宁博士研究生 081202-计算机软件与理论

尚田丰博士研究生 081202-计算机软件与理论

罗文娟博士研究生 081202-计算机软件与理论

李婷婷硕士研究生 081203-计算机应用技术

王群硕士研究生 081202-计算机软件与理论

董智硕士研究生 081202-计算机软件与理论

马云龙硕士研究生 430112-计算机技术

韩硕硕士研究生 081202-计算机软件与理论

余文超硕士研究生 081203-计算机应用技术

杜长营博士研究生 081202-计算机软件与理论

金鑫博士研究生 081202-计算机软件与理论

王浩成博士研究生 081202-计算机软件与理论

敖翔博士研究生 081202-计算机软件与理论

周干斌博士研究生 081202-计算机软件与理论

吴新宇硕士研究生 081202-计算机软件与理论

程晓虎硕士研究生 081202-计算机软件与理论

左罗硕士研究生 081202-计算机软件与理论

黄明硕士研究生 081202-计算机软件与理论

闫肃硕士研究生 081202-计算机软件与理论

罗丹硕士研究生 085212-软件工程

周英敏硕士研究生 081202-计算机软件与理论

现指导学生

何佳博士研究生 081202-计算机软件与理论

张钊博士研究生 081202-计算机软件与理论

陈敬伍硕士研究生 081202-计算机软件与理论

潘斐阳博士研究生 081202-计算机软件与理论

奚冬博硕士研究生 081202-计算机软件与理论

柳阳博士研究生 081202-计算机软件与理论

李硕凯博士研究生 081202-计算机软件与理论

罗玲硕士研究生 081202-计算机软件与理论

科研活动

课题组现在研项目

1、国家自然能科学基金重大项目：NSFC-广东省大数据科学研究中心项目: 基于超算的大数据分析处理基础算法与编程支撑环境，课题2: 大数据分析核心算法及其理论分析，批准号：U1811461, 执行期：2019.1.1-2023.12.31

2、国家自然科学基金重点项目U1836206, 项目名称：基于开放知识网络的特定目标隐含线索发现研究,起止时间：2019.1.1-2023.12.31

3、国家自然科学基金面上项目：深度与宽度自适应的深度极端学习机模型研究, No.61573335， 2016年01月至 2019年 12月，负责人

4. 国家自然科学基金一年期滚动项目NO.91846113，项目名称：一年期滚动项目——证券管理决策大数据挖掘云服务平台研究，2019.1.1-2019.1.231

5、国家自然科学基金面上项目：“基于深度学习的推荐算法”No. 61773361, 项目起止年月：2018年1 月至2021 年12 月

6、国家自然科学基金青年科学基金项目“序列大数据复杂情景模式发现算法研究”，No. 61602438，2017.1-2019.12

7、国家自然科学基金面上项目：深度与宽度自适应的深度极端学习机模型研究, No.61573335， 2016年01月至 2019年 12月

8、国家重点研发计划项目：大数据分析的基础理论和技术方法(2018YFB1004300)课题（2018YFB1004303）：多源不确定数据挖掘方法与技术，2018年月至2021年4月

9、国家重点研发计划项目（2017YFB1002104）：“大数据驱动的自然语言理解、问答和翻译”的课题五，No. 2017YFB1002104，分课题“基于大数据的面向开放域的智能问答技术”, 2017年10月至2021年09月

主持或参加完成的科研项目：

国家自然科学基金大数据重大计划培育项目：“证券管理决策大数据挖掘云服务平台研究” No. 91546122，2016年1 月至2018 年12 月，负责人，圆满完成，顺利结题。
国家自然科学基金面上项目“领域适应性问题相关学习算法与理论研究”，No. 61175052,2012.1-2015.12,负责人，圆满完成，顺利结题。
国家自然科学基金重点项目“WEB 搜索与挖掘的新理论与方法”，No. 60933004,2010.1-2013.12, 合作方负责人, 结题被评为优。
国家自然科学基金面上项目：分布式计算环境下的并行数据挖掘算法与理论研究，2010.1～2012.12，负责人，圆满完成，顺利结题。
国家自然科学基金面上项目“基于超曲面的覆盖分类算法与理论研究” No. 60675010，2007.1-2009.12 负责人，被评为优
国家自然科学基金“概念语义空间及其应用”No.60173017，负责人：何清，2001.1-2002.12，被评为优
国家“八六三”高技术研究发展计划项目“开放环境下海量web数据提取、集成、分析和管理系统平台与应用”所属课题“海量web数据内容管理、分析挖掘技术与大型示范应用” No.2012AA011003, 2012.1-2014.12。子课题负责人，结题获得好评。
国家“八六三”高技术研究发展计划“基于感知机理的智能信息处理技术”No：2006AA01Z128, 负责人，2006.9-2008.12，结题获得好评。
国家“八六三”高技术研究发展计划“自主计算的理论和技术研究”No：2003AA115220, 负责人， 2003.7-2005.10，结题获得好评。
973项目课题“非结构化信息(图像)的内容理解与语义表征”No. 2007CB311004，2007.7-2012.7，骨干，项目结题被评为优。

发表和录用论文情况

一、会议论文

[1]Dongbo Xi, Fuzhen Zhuang*, Yanchi Liu, Jingjing Gu, Hui Xiong, Qing He: Modelling of Bi-directional Spatio-Temporal Dependence and Users' Dynamic Preferences for Missing POI Check-in Identification. AAAI 2019.

[2]Feiyang Pan, Qingpeng Cai, An-Xiang Zeng, Chun-Xiang Pan, Qing Da, Hualin He, Qing He, Pingzhong Tang. Policy Optimization with Model-based Explorations. AAAI 2019.

[3]Feiyang Pan, Shuokai Li, Xiang Ao, Pingzhong Tang, Qing He. Warm Up Cold-start Advertisements : Improving CTR Predictions via Learning to Learn ID Embeddings. To appear in the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2019).

[4]Pan feiyang, Cai, Qi,Tang, Pingzhong, Zhuang, Fuzhen., He, Qing. Policy gradients for contextual recommendations,WWW2019

[5]Ying Sun, Fuzhen Zhuang, Hengshu Zhu, Xin Song, Qing He, Hui Xiong. A Structure-Aware Convolutional Neural Network Approach, KDD2019

[6]Ling Luo, Xiang Ao,Yan Song,Jinyao Li,Xiaopeng Yang,Qing He,Dong Yu, Unsupervised Neural Aspect Extraction with Sememes,IJCAI2019

[7]Ying Sun, Hengshu Zhu, Fuzhen Zhuang, Jingjing Gu and Qing He Exploring the Urban Region-of-Interest through the Analysis of Online Map Search Queries，KDD2018

[8]Ganbin Zhou, Ping Luo, Rongyu Cao, Yijun Xiao, Fen Lin, Bo Chen, Qing He. Tree-Structured Neural Machine for Linguistics-Aware Sentence Generation，The Thirty-Second AAAI Conference on Artificial Intelligence (AAAI-18) ，February 2–7, 2018，New Orleans, Lousiana, USA

[9]Ganbin Zhou, Ping Luo, Yijun Xiao, Fen Lin, Bo Chen, Qing He. Elastic Responding Machine for Dialog Generation with Mechanism Dynamically Selecting，The Thirty-Second AAAI Conference on Artificial Intelligence (AAAI-18) ，February 2–7, 2018，New Orleans, Lousiana, USA

[10]Jingwu Chen, Fuzhen Zhuang, Xin Hong, Xiang Ao, Xing Xie and Qing He: Attention-driven Factor Model for Explainable Personalized Recommendation. SIGIR 2018

[11]Xiang Ao, Yang Liu, Zhen Huang, Luo Zuo, Qing He. Free-rider Episode Screening via Dual Partition Model. The 23rd International Conference on Database Systems for Advanced Applications (DASFAA), 2018.

[12]Ling Luo, Xiang Ao, Feiyang Pan, Tong Zhao, Ningzi Yu, Qing He. Beyond Polarity: Interpretable Financial Sentiment Analysis with Hierarchical Query-driven Attention. The 27th International Joint Conference on Artificial Intelligence (IJCAI), 2018.

[13]Jia He, Changying Du, Changde Du, Fuzhen Zhuang, Qing He, Guoping Long.Nonlinear Maximum Margin Multi-view Learning with Adaptive Kernel,IJCAI17

[14]Ganbin Zhou, Ping Luo, Rongyu Cao, Fen Lin, Bo Chen, Qing He. Mechanism-Aware Neural Machine for Dialogue Response Generation，AAAI2017

[15]Xiang Ao, Ping Luo, Jin Wang, Fuzhen Zhuang, Qing He. Mining Precise-positioning Episode Rules from Event Sequences，ICDE2017

[16]Fuzhen Zhuang, Jing Zheng, Chuan Shi and Qing He.Transfer Collaborative Filtering from Multiple Sources via Consensus Regularization,WSDM2017

[17]Qing He, Yunlong Ma, Qun Wang, Fuzheng Zhuang, Zhongzhi Shi. Parallel Outlier Detection Using KD-Tree Based on MapReduce, IEEE CloudCom 2011,Washington, DC, USA, 4-9 July, 2011

[18]Qing He, Zhongzhi Shi, Lian Ren.The Classification Method Based on Hyper Surface，2002 International Joint Conference on Neural Networks，2002.5:1499-1503, Honolulu, Hawaii,USA, May 12-17, 2002

[19]Qing He, Xiurong Zhao, Sulan Zhang. Multi-modal services for web information collection based on multi-agent techniques, Lecture Notes in Computer Science, v 4088 LNAI, Agent Computing and Multi-Agent Systems: 9th Pacific Rim International Workshop on Multi-Agents, PRIMA 2006, p 129-137, Guilin, China, in August 2006

[20]Jia He, Changying Du, Fuzhen Zhuang,Yin Xin, Qing He*, Guoping Long. Online Bayesian Max-margin Subspace Multi-view Learning, IJCAI-16，July 9–15, 2016, New York

[21]Ping Luo, Ganbin Zhou, Qing He*. Browsing Regularities in Hedonic Content Systems: the More the Merrier? IJCAI-16，July 9–15, 2016, New York

[22]Xiang Ao, Ping Luo, Chengkai Li, Fuzhen Zhuang, Qing He*. Online Frequent Episode Mining, ICDE 2015 : International Conference on Data Engineering (ICDE15), Seoul, Korea, April 13-17, 2015

[23]Changying Du, Shandian Zhe, Fuzhen Zhuang, Alan Qi, Qing He*, Zhongzhi Shi. Bayesian Maximum Margin Principal Component Analysis, Twenty-Ninth AAAI Conference on Artificial Intelligence (AAAI-15)，Austin, Texas, USA, January 25–30, 2015,

[24]Xinyu Wu, Ping Luo, Qing He*, Tianshu Feng. Festival, Date and Limit Line: Predicting Vehicle Accident Rate in Beijing, SDM15, British Columbia, Canada, April 30-May 2

[25]Xiang Ao, Ping Luo, Chengkai Li, Fuzhen Zhuang, Qing He*, Zhongzhi Shi.Discovering and learning sensational episodes of news events. The 23rd international conference on World Wide Web, WWW2014, Seoul, Korea, April 7-11,

[26]Wenjuan Luo, Fuzhen Zhuang, Xiaohu Cheng, Qing He*, Zhongzhi Shi. Ratable Aspects over Sentiments: Predicting Ratings for Unrated Reviews, IEEE International Conference on Data Mining (ICDM 2014), Shenzhen, China,December 14-17, 2014

[27]Xin Jin, Fuzhen Zhuang, Hui Xiong, Changying Du, Ping Luo and Qing He*. Multi-task Multi-view Learning for Heterogeneous Tasks, CIKM’14, November 03–07, 2014, Shanghai, China

[28]Fuzhen Zhuang, Xiaohu Cheng, Sinno Jialin Pan, Wenchao Yu, Qing He*, Zhongzhi Shi. Transfer Learning with Multiple Sources via Consensus Regularized Autoencoders, The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML14/PKDD14), Nancy, France, September 15th to 19th, 2014.

[29]Changying Du, Jia He, Fuzhen Zhuang, Yuan Qi, Qing He*. Nonparametric Bayesian Multi-Task Large-margin Classification, 21st European Conference on Artificial intelligence (ECAI14), Prague, Czech, 18-22 Aug. 2014.

[30]Shuo Han, Fuzhen Zhuang, Qing He*, Zhongzhi Shi. Balanced Seed Selection for Budgeted Influence Maximization in Social Networks, PAKDD 2014: Pacific-Asia Conference on Knowledge Discovery and Data Mining , 2014-05-13, Tainan, Taiwan, China

[31]Xiang Ao, Ping Luo, Chengkai Li, Fuzhen Zhuang, Qing He*, Zhongzhi Shi. Discovering and learning sensational episodes of news events. The 23rd international conference on World Wide Web, WWW2014, Seoul, Korea,April 7-11

[32]Wenjuan Luo, Fuzhen Zhuang, Xiaohu Cheng, Qing He*, Zhongzhi Shi. Ratable Aspects over Sentiments: Predicting Ratings for Unrated Reviews, IEEE International Conference on Data Mining (ICDM 2014), Shenzhen, China / December 14-17, 2014

[33]Xin Jin, Fuzhen Zhuang, Hui Xiong, Changying Du, Ping Luo and Qing He*. Multi-task Multi-view Learning for Heterogeneous Tasks, CIKM’14, Shanghai, China, November 03–07, 2014

[34]Shuo Han, Fuzhen Zhuang, Qing He*, Zhongzhi Shi. Balanced Seed Selection for Budgeted Influence Maximization in Social Networks, PAKDD 2014 : Pacific-Asia Conference on Knowledge Discovery and Data Mining, Tainan, Taiwan, China,2014-05-13

[35]Fuzhen Zhuang, Ping Luo, Changying Du, Qing He*, Zhongzhi Shi. Triplex Transfer Learning: Exploiting both Shared and Distinct Concepts for Text Classification, WSDM’13, Rome, Italy, February 4–8, 2013

[36]Fuzhen Zhuang, Ping Luo, Peifeng Yin, Qing He*, Zhongzhi Shi. Concept Learning for Cross-domain Text Classification: a General Probabilistic Framework, 23rd International Joint Conference on Artificial Intelligence (IJCAI 2013). Beijing, China, August 3-9, 2013

[37]Tianfeng Shang, Qing He*, Fuzhen Zhuang and Zhongzhi Shi. A New Similarity Measure Based on Preference Sequence for Collaborative Filtering. Web Technologies and Applications. 15th Asia-Pacific Web Conference, APWeb 2013,Sydney, NSW, Australia, 4-6 April 2013

[38]Tianfeng Shang, Qing He*, Fuzhen Zhuang, Zhongzhi Shi. Extreme Learning Machine Combining Matrix Factorization for Collaborative Filtering. IEEE The 2013 International Joint Conference on Neural Networks, IJCNN 2013, Dallas, TX, USA, August 4-9, 2013.

[39]Xin Jin, Fuzhen Zhuang, Shuhui Wang, Qing He*, and Zhongzhi Shi. Shared Structure Learning for Multiple Tasks with Multiple Views, ECML/PKDD13, Prague, September 23-27, 2013

[40]Wenchao Yu, Guangxiang Zeng, Ping Luo, Fuzhen Zhuang,Qing He*, and Zhongzhi Shi. Embedding with Autoencoder Regularization, ECML/PKDD13, Prague,September 23-27, 2013

[41]Changying Du, Fuzhen Zhuang, Qing He* and Zhongzhi Shi. Multi-Task Semi-Supervised Semantic Feature Learning for Classification, ICDM2012，pp. 191-200, Brussels, Belgium, 2012 (12/10-12/13)

[42]Wenjuan Luo Fuzhen Zhuang, Qing He*, and Zhongzhi Shi. Quad-tuple PLSA: Incorporating Entity and Its Rating in Aspect Identification, The 16th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), PAKDD 2012, pp. 392–404, Kuala Lumpur, Malaysia, 29 May - 1 June,2012

[43]Xudong Ma, Ping Luo, FuzhenZhuang, Qing He*, Zhongzhi Shi and ZhiyongShen. Combining Supervised and Unsupervised Models via Unconstrained Probabilistic Embedding, Twenty-Second International Joint Conference on Artificial Intelligence, IJCAI 11，pp.1396-1401C,Barcelona in July 2011

[44]Fuzhen Zhuang, Ping Luo, Hui Xiong, Qing He*. Yuhong Xiong. Exploiting Associations between Word Clusters and Document Classes for Cross-domain Text Categorization, 2010 SIAM International Conference on Data Mining (SDM'2010), pp.13-24, Columbus, Ohio, April 19, 2010(EI,被大会推荐的十二篇最佳论文提名之一)

[45]Fuzhen Zhuang, Ping Luo, Zhiyong Shen, Qing He*, Yuhong Xiong, and Zhongzhi Shi. D-LDA: A Topic Modeling Approach without Constraint Generation for Semi-Defined Classification, accepted as a regular paper at the IEEE International Conference on Data Mining (ICDM 2010) to be held in Sydney Australia, December 14-17，2010, pp.709-718, (EI )

[46]Fuzhen Zhuang, Ping Luo, Zhiyong Shen, Qing He*, Yuhong Xiong, Zhongzhi Shi1, Hui Xiong. Collaborative Dual-PLSA: Mining Distinction and Commonality across Multiple Domains for Classification, The 19th ACM International Conference on Information and Knowledge Management( CIKM’10), October 26-30, 2010, Toronto, Canada. (获得八篇最佳论文提名之一, 并获得Student Travel Awards)

[47]Qing Tan, Qing He*, Zhongzhi Shi. Nonparametric Curve Extraction Based on Ant Colony System, Proceedings of the Twenty-Fourth AAAI Conference on Artificial Intelligence (AAAI-10), pp.599-604, Atlanta, USA, July 10-15, 2010

[48]Weizhong Zhao, Huifang Ma, Qing He.Parallel k-means clustering based on mapreduce, Cloud Computing, 2009

[49]Ping Luo, Fuzhen Zhuang, Hui Xiong, Yuhong Xiong, Qing He*. Transfer Learning from Multiple Source Domains via Consensus Regularization, full paper in CIKM 2008 , Napa Valley, California October 26-30, 2008 (EI)

[50]Qiuge Liu, Qing He*, Zhongzhi Shi. Extreme Support Vector Machine Classify, Lecture Notes in Computer Science, v 5012 LNAI, Advances in Knowledge Discovery and Data Mining, 12th Pacific-Asia Conference, PAKDD 2008, Proceedings, 2008, p 222-233,Osaka,Japan,May 20-23,2008(EI)

[51]Luo, Ping; Lu, Kevin; He, Qing*; Shi, Zhongzhi. A heterogeneous computing system for data mining workflows, Lecture Notes in Computer Science, v 4042 LNCS, Flexible and Efficient Information Handling - 23rd British National Conference on Databases, BNCOD 23, Proceedings, 2006, p 177-189, Belfast, Northern Ireland, UK, July 18-20, 2006

[52]Zheng, Zheng; He, Qing*; Shi, Zhongzhi. Granule sets based bilevel decision model, Lecture Notes in Computer Science, v 4062, Rough Sets and Knowledge Technology - First International Conference, RSKT 2006, Proceedings, 2006, p 530-537, Chongqing, China, July 24-26, 2006

[53]Zhao, Xiu-Rong; He, Qing*; Shi, Zhong-Zhi. HyperSurface Classifiers ensemble for high dimensional data sets, Lecture Notes in Computer Science, v 3971, Advances in Neural Networks - ISNN 2006: Third International Symposium on Neural Networks, p 1299-1304, Chengdu, China, May 28 - June 1, 2006

[54]Ping Luo, Qing He*, Rui Huang, Fen Lin, Zhongzhi Shi. Execution Engine of Meta-learning System for KDD in Multi-agent Environment. Lecture Notes in Computer Science. Springer-Verlag, Volume 3505 / 2005, 149-160. AIS-ADM 2005, St. Petersburg, Russia, June 6-8, 2005

[55]Ping Luo, Su Yan, Zhiqiang Liu, Zhiyong Shen, Shengwen Yang, Qing He. From Online Behaviors to Offline Retailing, the ACM KDD 2016 Conference as a full presentation（CCF A）

二、期刊论文

[1]Zhao Zhang, Fuzhen Zhuang, Xuebing Li, Zhengyu Niu, Jia He, Qing He, Hui Xiong: Knowledge Triple Mining via Multi-Task Learning. Information Systems, Information Systems 80 (2019) 64–75

[2]Xiang Ao, Haoran Shi, Jin Wang, Luo Zuo, Hongwei Li, Qing He. Large-scale Frequent Episode Mining from Complex Event Sequences with Hierarchies. ACM Transactions on Intelligent Systems and Technology (ACM TIST).

[3]Thapana Boonchooa, Xiang Ao*, Yang Liu, Weizhong Zhao, Fuzhen Zhuang, Qing He. Grid-based DBSCAN : Indexing and Inference. Pattern Recognition (PR), 90 : 271-284, 2019

[4]Zhou Ganbin Luo Ping He Qing. Predicting Compositional Time Series via Autoregressive Dirichlet Estimation, SCIENCE CHINA Information Sciences (accepted)

[5]Xiang Ao, Ping Luo, Jin Wang, Fuzhen Zhuang and Qing He. Mining Precise-positioning Episode Rules from Event Sequences, acceped by IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING

[6]Fuzhen Zhuang, Xuebing Li, Xin Jin, Dapeng Zhang, Lirong Qiu, Qing He: Semantic Feature Learning for Heterogeneous Multi-task Classification via Non-negative Matrix Factorization. IEEE Transactions on Cybernetics, 2017.

[7]Xuebing Li, Ying Sun, Fuzhen Zhuang, Jia He, Zhao Zhang, Shijun Zhu, Qing He: Potential Off-grid User Prediction System Based on Spark. ZTE Communications, 2018. (Accepted)

[8]Qing He, Haocheng Wang, Fuzhen Zhuang, Tianfeng Shang, Zhongzhi Shi. Parallel sampling from big data with uncertainty distribution, Fuzzy Sets and Systems 258 (2015) 117–133 (SCI)

[9]Qing He, Xin Jin, Changying Du, Fuzhen Zhuang and Zhongzhi Shi. Clustering in extreme learning machine feature space. Neurocomputing 128 : 88-95 (2014). (SCI).

[10]Qing He, Tianfeng Shang, Fuzhen Zhuang and Zhongzhi Shi. Parallel Extreme Learning Machine for Regression based on MapReduce, Neurocomputing 102(2013)52–58 (SCI\EI)

[11]He, Qing; Zhao, Weizhong; Shi, Zhongzhi. CHSMST: A clustering algorithm based on hyper surface and minimum spanning tree, Soft Computing, v 15, n 6, p 1097-1103, June 2011(SCI\EI)

[12]Qing He, Changying Du, Qun Wang, FuzhenZhuang, Zhongzhi Shi. A Parallel Incremental Extreme SVM Classifier, Neurocomputing，74 (2011) 2532–2540 (SCI\EI )

[13]Qing He, Xiurong Zhao, Zhongzhi Shi.Minimal consistent subset for Hyper Surface Classification method. INTERNATIONAL JOURNAL OF PATTERN RECOGNITION AND ARTIFICIAL INTELLIGENCE Volume: 22 Issue: 1 Pages: 95-108, FEB 2008.(SCI\EI)

[14]Qing He, Xiurong Zhao, Zhongzhi Shi. Classification based on dimension transposition for high dimension data，International Journal Soft Computing 11(4),2007, pp: 329 - 334(SCI)

[15]Qing He, Zhongzhi Shi,Li-an Ren, E.S. Lee. A Novel Classification Based on Hypersurface. International Journal of Mathematical and Computer Modeling 38(2003),395-407 (SCI)

[16]Qing He, Hongxing Li, Zhongzhi Shi, E.S.Lee. On Fuzzy Clustering Method Based on Perturbation. Computers and Mathematics with Applications, v 46, n 5-6, September, 2003, p 929-946 (SCI\EI)

[17]Qing He, Hongxing Li, C.L.P. Chen, E.S. Lee. Extension Principles and Fuzzy Set Categories. International Journal of Computers and Mathematics with Applications 2000, 39: 45-53(SCI)

[18]Jie Lu, Zheng Zheng, Guangquan Zhang, Qing He* and Zhongzhi Shi. A new solution algorithm for solving rule-sets based bilevel decision problems, CONCURRENCY AND COMPUTATION: PRACTICE AND EXPERIENCE. Vol: 27, No: 4,pages: 830-54 (SCI\EI)

[19]Wenjuan Luo, Fuzhen Zhuang, Weizhong Zhao, Qing He*, Zhongzhi Shi. QPLSA: Utilizing quad-tuples for aspect identification and rating, Information Processing and Management 51 (2015) 25–41(SCI\EI)

[20]Wenchao Yu, Fuzhen Zhuang, Qing He* and Zhongzhi Shi. Learning Deep Representations via Extreme Learning Machine, Neurocomputing, Volume 149, Part A, 3 February 2015, Pages 308-315 (SCI\EI)

[18]Xiang Ao; Ping Luo; Xudong Ma; Fuzhen Zhuang; Qing He*; Zhongzhi Shi; Zhiyong Shen. Combining Supervised and Unsupervised Models via Unconstrained Probabilistic Embedding, Information Sciences, 257 (2014) 101–114. (SCI impact factor (2012): 3.643)

[21]Fuzhen Zhuang, Ping Luo, Changying Du, Qing He*, Zhongzhi Shi, Hui Xiong: Triplex transfer learning: exploiting both shared and distinct concepts for text classification, IEEE TRANSACTIONS ON CYBERNETICS, VOL. 44, NO. 7, 1191-1203, JULY 2014 (impact factor (2012): 3.236) (SCI\EI)

[22]Shuo Han, Fuzhen Zhuang, Qing He*, Zhongzhi Shi, & Xiang Ao. Energy model for rumor propagation on social networks. Physica A: Statistical Mechanics and its Applications，394 (2014) 99–109 (SCI impact factor (2012): 1.676).

[23]Shuo Han，Qing He*，Zhongzhi Shi. Energy Model for Rumor Propagation on Social Networks. Physica A: Statistical Mechanics and its Applications，394 (2014) 99–109.

[24]Wenjuan Luo, Fuzhen Zhuang, Qing He*, Zhongzhi Shi Exploiting relevance, coverage, and novelty for query-focused multi-document summarization，Knowledge-Based Systems. Volume 46, July 2013, Pages 33–42 . (SCI\EI)

[25]Fuzhen Zhuang, Ping Luo, Zhiyong Shen, Qing He*, Yuhong Xiong, Zhongzhi Shi and Hui Xiong. Mining Distinction and Commonality across Multiple Domains using Generative Model for Text Classification, IEEE Transactions on Knowledge and Data Engineering, VOL. 24, NO. 11, NOVEMBER 2012,2025-2039(SCI\EI )

[26]Zhiping Shi, Xi Liu, Qingyong Li, Qing He*, Zhongzhi Shi, Extracting Discriminative Features for CBIR, MULTIMEDIA TOOLS AND APPLICATIONS， Volume 61, Number 2 (2012), 263-279(SCI)

[27]Fuzhen Zhuang, George Karypis, Xia Ning, Qing He*, Zhongzhi Shi. Multi-view learning via probabilistic latent semantic analysis, Information Sciences,199 (2012) 20–30(SCI\EI)

[28]Weizhong Zhao, Qing He*, Huifang Ma, Zhongzhi Shi. Effective Semi-supervised Document Clustering via Active Learning with Instance-level Constraints, Knowledge and Information Systems (2012) 30:569–587 (SCI\EI)

[29]Tan, Qing; He, Qing*; Zhao, Weizhong; Shi, Zhongzhi; Lee, E.S. An improved FCMBP fuzzy clustering method based on evolutionary programming, Computers and Mathematics with Applications, v 61, n 4, p 1129-1144, February 2011(SCI\EI)

[30]Guang-Quan Zhang, ZhengZheng, Jie Lu, Qing He*. An Algorithm for Solving Rule-Sets Based Bilevel Decision Problems, COMPUTATIONAL INTELLIGENCE Vol.27 No.2 pp.235-259, 2011 (SCI\EI)

[31]Fuzhen Zhuang, Ping Luo, Hui Xiong, Yuhong Xiong, Qing He*, and Zhongzhi Shi. Cross-Domain Learning from Multiple Sources: A Consensus Regularization Perspective, IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING, December 2010 (vol. 22 no. 12) ,pp. 1664-1678 (SCI\EI)

[32]Zheng, Z., Lu, J, Zhang G, He Q*, Rule sets based bilevel decision model and algorithm, Expert Systems with Applications, 2009. Vol. 36, No. 1, 18-26(SCI)

[33]Shifei Ding, Yongping Zhang, Xiaofeng Lei, Xinzheng Xu, Xin Wang, Li Wang, Qing He*. Research on a principal components decision algorithm based on information entropy, Journal of Information Science, Vol. 35, No. 1, 120-127 (2009) (SCI)

[34]Zhuang F Z, Luo P, He Q, et al. Inductive transfer learning for unlabeled target-domain via hybrid regularization. Chinese Sci Bull, 2009, 54: 2470―2478 (SCI)

[35]Zhiping Shi, Qing He*, Zhongzhi Shi. An Index and Retrieval Framework Integrating Perceptive Features and Semantics for Multimedia Database. Multimedia Tools and Application (2009) 42:207–231 Springer (SCI)

[36]Zheng, Z., Lu, J, Zhang G, He Q*, Rule sets based bilevel decision model and algorithm, Expert Systems with Applications, 2009. Vol. 36, No. 1, 18-26(SCI)

[37]Ping Luo, Guoxing Zhan, Qing He*, Zhongzhi Shi, and Kevin Lu, On Defining Partition Entropy by Inequalities. IEEE TRANSACTIONS ON INFORMATION THEORY, v53, n 9, SEPTEMBER 2007, p 3233-3239.（SCI）

[38]Ping Luo; Lu, Kevin; Shi, Zhongzhi; He, Qing*. Distributed data mining in grid computing environments. Future Generation Computer Systems, v 23, n 1, Jan 1, 2007, p 84-91(SCI\EI)

[39]Zhongzhi Shi; Huang, Youping; He, Qing*; Xu, Lida; Liu, Shaohui; Qin, Liangxi; Jia, Ziyan; Li, Jiayou; Huang, Huijing; Zhao, Lei. MSMiner-a developing platform for OLAP. Decision Support Systems, v 42, n 4, January, 2007, Decision Support Systems in Emerging Economies, pp. 2016-2028(SCI)

[40]Luo, Ping; Lu, Kevin; Shi, Zhongzhi; He, Qing*. Distributed data mining in grid computing environments, Future Generation Computer Systems, v 23, n 1, Jan 1, 2007, p 84-91

[41]Luo, Ping; Lu, Kevin; Huang, Rui; He, Qing*; Shi, Zhongzhi. A heterogeneous computing system for data mining workflows in multi-agent environments, Expert Systems, v 23, n 5, November, 2006, p 258-271(SCI\EI)

[42]Shi, Zhongzhi; Huang, Youping; He, Qing*; Xu, Lida; Liu, Shaohui; Qin, Liangxi; Jia, Ziyan; Li, Jiayou; Huang, Huijing; Zhao, Lei. MSMiner-a developing platform for OLAP, Decision Support Systems v 42,n 4,2007 p 2016-2028(SCI\EI)