基本信息

何清  男  博导  中国科学院计算技术研究所
电子邮件: heq@ics.ict.ac.cn
通信地址: 北京市海淀区科学院南路六号中科院计算技术研究所智能信息处理重点实验室
邮政编码: 100190

研究领域

机器学习、数据挖掘、文本挖掘、基于云计算的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,30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~现在, 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
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
2003-06-01-今,中国人工智能学会知识工程与分布智能专业委员会, 秘书长

教授课程

人工智能基础
认知计算
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. 一种异构数据表的合并方法及其系统,发明,2010,专利号:200910077659.6
2. 一种采用决策树的数据分类方法和系统,发明,2011,专利号:201110143821.7
3. 一种确定数据样本类别的方法及其系统 ,发明,2010,专利号:200910077994.6
4. 一种关联规则挖掘方法及其系统 ,发明,2010,专利号:200910077996.5
5. 一种数据挖掘系统中数据聚类的方法、系统及装置,发明,2011,专利号:201010102976.1
6. 一种数据处理方法及其系统,发明,2010,专利号:200910077660.9
7. 数据关联规则挖掘实现方法与系统,发明,2011,专利号:200910091865.2
8. 聚类实现方法及系统 ,发明,2011,专利号:200910091864.8
9. 聚类实现方法及系统,发明,2011,专利号:200910091866.7
10. 一种基于MapReduce的分布式垂直交叉网络爬虫系统,发明,2013,专利号:201310146080.7
11. 一种面向大数据的分布式单路径聚类主题发现算法,发明,2013,专利号:201310526790.2
12. 一种用于大数据的基于超曲面的分类方法及系统,发明,2013,专利号:201310727192.1

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

科研活动


课题组在研国家项目

( 1 ) 国家863计划:“面向政府管理的大数据内容理解与智能服务”主题项目子课题“大数据并行挖掘关键技术研究”, 2014-01--2016-12
( 2 ) 国家自然科学基金面上项目:“证券管理决策大数据挖掘云服务平台研究”No. 91546122, 主持, 国家级, 2016-01--2018-12
( 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,61573335, 主持, 国家级, 2016-01--2019-12
( 4 ) 国家自然科学基金面上项目:分类体系不确定的机器学习研究,  2015-01--2018-12
( 5 ) 国家自然科学基金面上项目:面向异构环境的多任务多视图学习算法研究,  2015-01--2018-12
( 6 ) 广东省省级科技计划项目:电信大数据分析及应用示范,No.2015B010109005,2015.05.01 -2018.12.31

指导学生情况

何清获得2007年所长奖教金,他所指导的学生多人获得科学院和计算所奖励,学生毕业后就业情况很好。

已毕业学生

赵秀荣是2004级硕士研究生,于2007年获得计算机软件与理论专业硕士学位。在学期间,她发表SCI、EI收录论文5篇,获得中国科学院刘永龄奖学金(全院50人),2007年毕业后到国家外汇管理局在北京工作。

刘秋阁是2005级硕士研究生,2008年获得计算机软件与理论专业硕士学位。在学期间,他在PAKDD08发表长文一篇(长文占录用文章的12%),并获得赴日本参会奖励(共10名),2008年毕业后到腾讯研究院在北京工作。

赵卫中是2007级博士研究生,2010年获得计算机软件与理论专业博士学位。在学期间,他发表国外SCI期刊和计算机学报等EI收录论文6篇,获得2009年北纬通讯奖学金,2010年优秀毕业生称号,2010年毕业后去湘潭大学工作,2012年去美国做博士后工作。

李金成是2007级硕士研究生,2010年获得计算机软件与理论方向硕士学位。他在学期间发表三篇论文被EI收录,获得2010年所长优秀奖,现在深圳证券所工作。

庄福振是2006级硕博研究生 2011年获得计算机软件与理论专业博士学位。在学期间他在IEEETKDE,InformationScience,Chinese Science Bulletin, CIKM2010,SDM2010、ICDM2010等期刊和会议发表论文,2008年获得度夏培肃奖,2011年获得中国科学院院长奖学金优秀奖,2013年获得中国人工智能学会优秀博士论文奖。在学期间赴香港科技大学学习2个月,并获得国家留学基金资助前往明尼苏达大学学习半年。2011年7月留在计算所工作,2013年任副研究员。

马旭东是2008级硕士研究生, 2011年获得计算机软件与理论专业硕士学位。在学期间,他获得2010年腾迅优秀奖,在2011年在人工智能顶级国际会议IJCAI2011上发表论文一篇,毕业后前往Google工作,现在美国Google总部工作。

李婷婷是2009级硕士研究生, 2011年获得计算机软件与理论专业硕士学位。在学期间,她发表两篇EI收录论文,2011年毕业后到中国银行在北京工作。

谭庆是2008级博士研究生, 2012年获得计算机软件与理论专业博士学位。在学期间,他在AAAI10和IJCMA等国际会议和期刊上发表论文4篇, 获得2010年北纬通信博士生奖,2012年2月毕业后到阿里云在北京工作。

王 群是2009级硕士研究生,2012年获得计算机软件与理论专业硕士学位,发表EI收录论文2篇,2010年获得北纬通信硕士生奖,2012年毕业到人民网工作,现在高德公司在北京工作。

罗文娟是2008级计算机软件与理论专业硕博研究生, 她在SCI国际期刊KBS和AIRS2010、PAKDD2012等会议上发表论文4篇,2013年毕业后到人人网在北京工作。

董智是2010级计算机软件与理论专业硕博连读研究生,已发表EI收录文章2篇,2013年毕业后到新华网,在北京工作。

马云龙是计算机应用技术专业2010级硕士研究生,已发表EI收录文章1篇,2011年获得北纬通信硕士生奖,2013年毕业后到中国科学院信息工程研究所,在北京工作。 



李宁是2009级计算机软件与理论专业博士研究生,已在IJNDC,SNPD2012等期刊和会议发表EI收录的论文4篇,国内核心论文2篇,现在北京高校工作。

尚田丰是2010级计算机软件与理论专业博士研究生,已在SCI国际期刊NeuroComputing发表论文1篇,并已在APWeb13、IJCNN13上发表论文,2012年获得北纬通信博士生奖。现在新加坡管理大学做博士后。


韩硕是2011级计算机软件与理论专业硕士研究生,在Physica A和PAKDD14上发表论文两篇,2013年获得北纬通讯奖学金。现在北京亚马逊公司工作。

余文超是2011级计算机软件与理论专业硕士研究生,在ECMLPKDD13、NeuroComputing上发表录用论文3篇,2013年获得计算所所长优秀奖,现在美国那卡罗莱纳大学读博士。


杜长营是2009级计算机软件与理论专业硕博连读研究生,2015年博士毕业。他已在NeuroComputing发表SCI收录论文, 并在ICDM12上发表长文一篇,获得2010年所长优秀奖,现在中国科学院软件所工作。

金鑫是2011级计算机软件与理论专业博士研究生,已在SCI国际期刊NeuroComputing、AMC发表论文2篇,并在ECMLPKDD13发表论文(oral+poster),2013年获得所长优秀奖,2015年博士毕业,现在华为公司北京工作。

敖翔是2010级硕博连读研究生,2012年9月转博,在Information Sciences、WWW14等期刊和会议上发表论文3篇,申请专利1项,2013年获得腾讯奖学金特等奖,获得2014年国家奖学金,2015年博士毕业,现留所工作。


吴新宇是2012级计算机软件与理论硕士研究生,申请了专利两项,2013年获得了计算所技术创新大赛奖项,获得中国科学院计算技术研究所硕士所长奖学金,现在IBM北京工作。 


程晓虎是2012级计算机软件与理论专业硕士研究生,IJCAI15、FSKD14发表论文一篇,获得中国科学院计算技术研究所斯伦贝谢硕士生奖学金,现在腾讯北京工作。


王浩成是2012级计算机软件与理论专业博士研究生,在Fuzzy Sets and Systems、IDA、SNPD2014、ELM2015上发表论文。 获得2015年度所长优秀奖博士生奖,现在北京市公安局工作。


闫肃是2013级计算机软件与理论专业硕士研究生,在IJCAI15合作发表论文一篇,现在腾讯工作。

罗丹是2013级计算机软件与理论专业硕士研究生,在ICDM2015合作发表论文一篇,现在微软工作。 

现在学学生


周干斌是2013级计算机软件与理论专业直博研究生,在IJCAI15,KDD16发表论文两篇。

何佳是2014级计算机软件与理论专业直博研究生,在IJCAI-16,IJCAI17发表论文两篇。

黄明是2014级计算机软件与理论专业硕士研究生 

左罗是2014级计算机软件与理论专业硕士研究生


周英敏  硕士研究生  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  

发表论文

一、会议论文

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

[2]   Ganbin Zhou, Ping Luo, Rongyu Cao, Fen Lin, Bo Chen, Qing He.Mechanism-Aware Neural Machine for Dialogue Response GenerationAAAI2017

[3]   Xiang Ao, Ping Luo, Jin Wang, Fuzhen Zhuang, Qing He. Mining Precise-positioning Episode Rules from Event SequencesICDE2017

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

[5]   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

[6]   Qing He, Zhongzhi Shi, Lian Ren.The Classification Method Based on Hyper Surface2002 International Joint Conference on Neural Networks2002.5:1499-1503, Honolulu, Hawaii,USA, May 12-17, 2002

[7]   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

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

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

[10]     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

[11]     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,

[12]     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

[13]     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,

[14]     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

[15]     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

[16]     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.

[17]     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.

[18]     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

[19]     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

[20]     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

[21]     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

[22]     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

[23]     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

[24]     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

[25]     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

[26]     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.

[27]     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

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

[29]     Changying Du, Fuzhen Zhuang, Qing He* and Zhongzhi Shi. Multi-Task Semi-Supervised Semantic Feature Learning for Classification, ICDM2012pp. 191-200, Brussels, Belgium, 2012 (12/10-12/13)

[30]     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

[31]     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 11pp.1396-1401C, Barcelona in July 2011

[32]     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)

[33]     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 14-172010, pp.709-718, (EI )

[34]     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)

[35]     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

[36]     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)

[37]     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)

[38]     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

[39]     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 

[40]     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

[41]     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

 

二、期刊论文

[1]   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)

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

[3]   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)

[4]   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)

[5]   Qing He, Changying Du, Qun Wang, FuzhenZhuang, Zhongzhi Shi. A Parallel Incremental Extreme SVM Classifier, Neurocomputing74 (2011) 2532–2540 (SCI\EI )

[6]   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)

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

[8]   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)

[9]   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)

[10]     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)

[11]     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)

[12]     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)

[13]     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)

[14]     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)

[15]     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)

[16]     Shuo Han, Fuzhen Zhuang, Qing He*, Zhongzhi Shi, & Xiang Ao. Energy model for rumor propagation on social networks. Physica A: Statistical Mechanics and its Applications394 (2014) 99–109 (SCI impact factor (2012): 1.676).

[17]     Shuo HanQing He*Zhongzhi Shi. Energy Model for Rumor Propagation on Social Networks. Physica A: Statistical Mechanics and its Applications394 (2014) 99–109.

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

[19]     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 )

[20]     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)

[21]     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)

[22]     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)

[23]     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)

[24]     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)

[25]     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)

[26]     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)

[27]     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)

[28]     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)

[29]     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)

[30]     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)

[31]     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

[32]     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)

[33]     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)

[34]     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

[35]     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)

[36]     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)