何清  研究员  

研究方向:机器学习;大数据挖掘等

所属部门:智能信息处理重点实验室

导师类别:博导计算机软件与理论

联系方式:heqing@ict.ac.cn 电话:010-62600542 手机:13910062653

个人网页:http://people.ucas.edu.cn/~heqing

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

1997年8月-2000年7月 北京师范大学 应用数学专业,模糊数学与人工智能方向 博士毕业,获博士学位

 

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.

 

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

个人主页的链接:http://people.ucas.edu.cn/~heqing

主要论著:

 

会议论文

[1]Dongbo Xi, Fuzhen Zhuang, Bowen Song, Yongchun Zhu, Shuai Chen, Dan Hong, Tao Chen, Xi Gu, Qing He. Neural Hierarchical Factorization Machines for User's Event Sequence Analysis. SIGIR20, July 25-30, 2020, Xi'an, China. 

[2]Dongbo Xi, Fuzhen ZhuangGanbin ZhouXiaohu ChengFen LinQing He. Domain Adaptation with Category Attention Network for Deep Sentiment Analysis. WWW’20, April 2024, 2020, Taipeipp.: 3133-3139.

[3]Feiyang Pan, Xiang Ao, Pingzhong Tang, Min Lu, Dapeng Liu, Lei Xiao and Qing He. Field-aware calibration: a simple and empirically strong method for reliable probabilistic predictions. WWW’20, April 2024, 2020, Taipei

[4]Qiwei ZhongYang LiuXiang AoBinbin HuJinghua FengJiayu TangQing He. Financial Defaulter Detection on Online Credit Payment via Multi-view Attributed Heterogeneous Information NetworkWWW’20, April 2024, 2020, Taipei

[5]Yongchun Zhu, Dongbo Xi, Bowen Song, Fuzhen Zhuang, Shuai Chen, Gu Xi, and Qing He. Modeling Users’ Behavior Sequences with Hierarchical Explainable Network for Cross-domain Fraud Detection. Proceedings of the Web Conference 2020. pp.: 928-938. WWW’20, April 2024, 2020, Taipei

[6]Zhao Zhang, Fuzhen Zhuang*, Hengshu Zhu, Zhiping Shi, Hui Xiong, Qing He, Relational Graph Neural Network with Hierarchical Attention for Knowledge Graph Completion. AAAI 2020, Feb.7-12,Newyork USA.

[7]Dongbo Xi, Fuzhen Zhuang, Yanchi Liu, Jingjing Gu, Hui Xiong, Qing He. Modeling Users’ Behavior Sequences with Hierarchical Explainable Network for Cross-domain Fraud Detection[C]// WWW’20, April 2024, 2020, Taipei

[8]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.

[9]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.

[10]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). 

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

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

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

[14]Ying Sun, Hengshu Zhu, Fuzhen Zhuang, Jingjing Gu and Qing He Exploring the Urban Region-of-Interest through the Analysis of Online Map Search QueriesKDD2018

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

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

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

[18]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.

[19]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.

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

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

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

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

[24]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

[25]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

[26]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

[27]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

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

[29]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

[30]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,

[31]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

[32]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,

[33]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

[34]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

[35]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.

[36]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.

[37]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

[38]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

[39]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

[40]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

[41]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

[42]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

[43]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

[44]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

[45]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.

[46]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

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

[48]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)

[49]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

[50]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

[51]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)

[52]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 )

[53]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)

[54]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

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

[56]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)

[57]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)

[58]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

[59]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 

[60]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

[61]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

[62]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 presentationCCF A

 

期刊论文

[1]Fuzhen Zhuang, Yingmin Zhou, Haochao Ying, Fuzheng Zhang, Xiang Ao, Xing Xie, Qing He, Hui Xiong: Sequential Recommendation via Cross-domain Novelty Seeking Trait Mining. Accepted by Journal of Computer Science and Technology, 2020.

[2]Jia HeOnline Bayesian Max-margin Subspace Learning for Multi-view Classification and Regression, Accepted by Machine Learning.

[3]Jingwu Chen, Fuzhen Zhuang, Tianxin Wang, Leyu Lin, Feng Xia, Lihuan Du, Qing He. Follow the Title then Read the Article: Click-guide Network for Dwell Time Prediction, Accepted by IEEE Transactions on Knowledge and Data Engineering

[4]Yang Liu, Xiang Ao, Linfeng Dong, Chao Zhang, Jin Wang, Qing He. Spatiotemporal Activity Modeling via Hierarchical Cross-Modal Embedding. Accepted by IEEE Transactions on Knowledge and Data Engineering. 2020.

[5]Yongchun Zhu, Fuzhen Zhuang, Jindong Wang, Guolin Ke, Jingwu Chen, Jiang Bian, Hui Xiong, Qing He: Deep Subdomain Adaptation Network for Image Classification. IEEE Transactions on Neural Networks and Learning Systems.

[6]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

[7]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). 

[8]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

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

[10]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

[11]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.

[12]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)

[13]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)

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

[15]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)

[16]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)

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

[18]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)

[19]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)

[20]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)

[21]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)

[22]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)

[23]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)

[24]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)

[25]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)

[26]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)

[27]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)

[28]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).

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

[30]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)

[31]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 )

[32]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)

[33]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)

[34]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)

[35]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)

[36]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)

[37]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)

[38]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)

[39]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)

[40]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)

[41]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)

[42]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)

[43]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

[44]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)

[45]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)

[46]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

[47]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)

[48]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)

 

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, 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, 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, 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, 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, 1 作者, 专利号: 200910091865.2

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

7 聚类实现方法及系统, 发明, 2011, 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, 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, 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, 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, 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, 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, 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

1PAKDD2018国际会议最有影响论文奖一等奖其他, 2018
2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
3北京市科学技术奖——主体网格智能平台三等奖省级, 2006

科研项目:

主持或参加完成的科研项目:

1.  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 201601月至 2019 12月,负责人

2.  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

3.  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. 915461222016月至201812月,负责人,圆满完成,被评为优。。     

4.  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。

5.  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。

6.  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,2010.12012.12,负责人,圆满完成,顺利结题。

7.  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. 606750102007.1-2009.12 负责人,被评为优

8.  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

9.  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。

10. 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”No2006AA01Z128, 负责人,2006.9-2008.12,结题获得好评。

11. 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”No2003AA115220, 负责人, 2003.7-2005.10,结题获得好评。

12. 973项目课题非结构化信息(图像)的内容理解与语义表征”No. 2007CB3110042007.7-2012.7,骨干,项目结题被评为优。

科研项目

1  智能问答关键技术研究及其在体育领域的应用实现, 主持国家级, 2017-10--2021-09
2  大数据分析核心算法及其理论分析-大数据分类算法, 主持国家级, 2019-01--2022-12
3  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:多源不确定数据挖掘方法与技术, 参与国家级, 2018-01--2021-04

获奖及荣誉:

(1)PAKDD2018国际会议最有影响论文奖, 一等奖, 其他, 2018

(2)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

(3)北京市科学技术奖——主体网格智能平台, 三等奖, 省级, 2006