西安交通大学电子与信息工程学院导师教师师资介绍简介-刘均

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English C.V. - 刘均Dr. Jun Liu

E-mail: liukeen(at)xjtu.edu.cn

Honors and Awards
2019, Wang Kuancheng Education Award
2018, Best Paper Award (NASAC 2018)
2018, Best Paper Award (ICBK 2018)
2018, Best Student Paper Award Candidate (ISWC 2018)
2016, Best Paper Award (The 27th ISSRE)
2014, IEEE Outstanding Service Award (The 14th IEEE CIT)
2013, Google Faculty Award
2010, IBM-CHINA Outstanding Teacher Award
2010, Young Scientist Award of ShaanXi Province
2009, National Second-class Award for Teaching
2008, New Century Excellent Talent of the Education Ministry of China
2006, Second Class Award for National Progress in Science and Technology
2004, Second Class Award of Progress in Science and Technology of the Education Ministry of China
2004, First Class Award of Progress in Science and Technology of shanghai City
2003, First Class Award of Progress in Science and Technology of Shaanxi Province
2003, “Hu’s” Scholarship in XJTU

Positions
Professor
Department of Computer Science
School of Electronic and Information Engineering
Xi’an Jiaotong University (XJTU), Xi’an 710049, China
Director
Shaanxi Province Key Lab. of STN Tech. R&D;
Institute of Multimedia Knowledge Fusion and Engineering.
Associate Editor: IEEE TNNLS (2020 ~)；Board Member: Internet of Things and Cyber-Physical Systems
Guest Editor: Information Fusion, ACM TOMM, IEEE Systems Journal, Future Generation Computer Systems
IEEE Senior Member, CCF Senior Member

Education and Work Experiences
12/2011–present Professor, Department of Computer Science and Technology, XJTU, China
7/2019–8/2019Senior Visiting Fellow,Karlsruhe Institute of Technology (KIT),Germany
8/2017–9/2017Senior Visiting Fellow,StanfordUniversity,USA
7/2016–8/2016 Senior Visiting Fellow,QueenslandUniversity,Australia
7/2011–8/2011 Visiting Scholar, Iowa State University, USA
7/1998–12/2011Lecturer,Assoc. Prof., Department of Computer Science, XJTU, China
5/2005–8/2005Visiting Scholar, University of Hong Kong, Hong Kong, China
9/1999–3/2004 Ph.D., Systems Engineering,XJTU, China
9/1995–7/1998M.Eng., Computer Architecture,XJTU, China
9/1991–7/1995B.Eng., Computer Science and Technology,Xi’an Jiaotong University(XJTU), China

Research Projects
1/2020–10/2020 Intelligent Tutoring Systems based on Knowledge Forest, funded by Lenovo Research
5/2018–4/2021 Educational Data Analysis and Mining for Smart Education, funded by the National Key Research and Development Program of China (2018YFB**)
1/2017–12/2020 Faceted Fusion of Knowledge Fragments from Open Knowledge Sources, funded by the National Natural Science Foundation of China (**)
1/2016–12/2020 Massive Online Collaborative Learning, funded by the National Natural Science Foundation of China (**)
1/2012–12/2014 Content Management and Analysis of Massive Web Data, funded by the Hi-Tech R&D (National 863) Project of China (2012AA011003)
7/2008–7/2010 Knowledge Discovery and Value-added Service in the field of Education, funded by the Hi-Tech R&D (National 863) Project of China (2008AA01Z131)
1/2009–12/2011 Mining Knowledge Elements and their Association from Domain-specific Text,funded by the National Natural Science Foundation of China (**)
1/2012–12/2015 Topology and evolution characteristics of knowledge map,funded by the National Natural Science Foundation of China (**)
Research Interests: NLP, CV, e-learning

Selected Publications
2021:
Book/Book Chapter
郑庆华、刘均、魏笔凡、张玲玲.知识森林：理论、方法与实践, 科学出版社, 2021.
Jun Liu, Lingling Zhang, Bifan Wei, Qinghua Zheng. Virtual Teaching Assistants: Technologies, Applications and Challenges. In: Fang Chen, JianlongZhou (Eds.), Humanity Driven AI: Productivity, Well-being, Sustainability and Partnership, Springer, 2021.
Journal Papers
Qika Lin, Jun Liu, Yudai Pan, Lingling Zhang, Xin Hu, Jie Ma.Rule-Enhanced Iterative Complementation for Knowledge Graph Reasoning, Information Sciences, 2021, Accepted.
Jie Ma, Jun Liu, Yaxian Wang, Junjun Li, and Tongliang Liu. Relation-aware Fine-grained Reasoning Network for Textbook Question Answering, IEEE Transactions on Neural Networks and Learning Systems, 2021, Accepted.
Lingling Zhang, Shaowei Wang, Xiaojun Chang, Jun Liu, Zongyuan Ge, and Qinghua Zheng. Auto-FSL: Searching the Attribute Consistent Network for Few-Shot Learning, IEEE Transactions on Circuits and Systems for Video Technology, 2021, Accepted.
Hongwei Zeng,Zhuo Zhi, Jun Liu, Bifan Wei. Improving Paragraph-level Question Generation with Extended Answer Network and Uncertainty-aware Beam Search. Information Sciences, 2021, Accepted.
Hongwei Zeng, Jun Liu, Meng Wang, Bifan Wei. A Sequence to Sequence Model for Dialogue Generation with Gated Mixture of Topics. Neurocomputing, 2021, Accepted.
Yanxiang Ling, Fei Cai, Xuejun Hu, Jun Liu, Wanyu Chen, and Honghui Chen. Context-Controlled Topic-Aware Neural Response Generation for Open-Domain Dialog Systems. Information Processing & Management, 2021, 58(1): 102392.
Conference Papers
Yanzhang Lyu, Hongzhi Yin, Jun Liu, Mengyue Liu, Huan Liu, Shizhuo Deng. Reliable Recommendation with Review-level Explanations. ICDE 2021.
2020:
Book/Book Chapter
Yao S., Wang R., Sun S., Bu D., Liu J. Joint Embedding Learning of Educational Knowledge Graphs. In: Pinkwart N., Liu S. (eds) Artificial Intelligence Supported Educational Technologies. Advances in Analytics for Learning and Teaching. Springer, 2020.
Journal Papers
Lingyun Song, Jun Liu, Mingxuan Sun, Xuequn Shang.Weakly Supervised Group Mask Network for Object Detection. International Journal of Computer Vision (IJCV), 2020, Accepted.
麻珂欣, 魏笔凡, 马杰, 刘均, 黄毅, 胡珉, 冯俊兰. 知识主题间先序关系挖掘, 大数据, 2020, 已录用.
姚思雨,赵天哲, 王瑞杰. 刘均.规则引导的知识图谱联合嵌入方法, 计算机研究与发展, 2020, 已录用.
Bei Wu; Bifan Wei, Jun Liu, Kewei Wu, Meng Wang, Faceted Text Segmentation via Multi-Task Learning,IEEE Transactions on Neural Networks and Learning Systems, 2020, Accepted.
Xin Hu, Jun Liu, Jie Ma, Yudai Pan, Lingling Zhang, Fine-grained 3D-Attention Prototypes for FewShot Learning, Neural Computation, 2020, 32(9): 1664-1684.
Chenxu Wang, Wei Rao, Wenna Guo, Pinghui Wang, Jun Liu, Xiaohong Guan,Towards Understanding the Instability of Network Embedding, IEEE Transactions on Knowledge and Data Engineering, 2020, Accepted.
Lingling Zhang, Xiaojun Chang, Jun Liu, Minnan Luo, Mahesh Prakash, Alexander Hauptmann, Few-Shot Activity Recognition with Cross-Modal Memory Network, Pattern Recognition, 2020, 108: 107348.
范铭, 刘烃, 刘均, 罗夏朴, 于乐, 管晓宏.安卓恶意软件检测方法综述, 中国科学: 信息科学, 2020, 50(8): 1148-1177.
Conference Papers
Lingling Zhang, Xiaojun Chang, Jun Liu, Sen Wang, Zongyuan Ge, Minnan Luo, Alexander Hauptmann, ZSTAD: Zero-Shot Temporal Activity Detection, CVPR2020.
2019:
Journal Papers
Ruijie Wang; Meng Wang; Jun Liu; Michael Cochez. Structured Query Construction via Knowledge Graph Embedding,Knowledge and Information Systems,2019, Accepted.
Lingling Zhang, Minnan Luo, Jun Liu, Xiaojun Chang, Yi Yang, and Alexander G. Hauptmann. Deep Top-k Ranking for Image-Sentence Matching, IEEE Transaction on Multimedia, 2019, 22(3): 775-785.
Lingling Zhang, Jun Liu, Minnan Luo, Xiaojun Chang, Qinghua Zheng, Alexander G. Hauptmann,Scheduled Sampling for One-Shot Learning via Matching Network, Pattern Recognition, 2019, 96: 106962.
Qinghua Zheng, Jun Liu, Hongwei Zeng, Zhaotong Guo, Bei Wu & Bifan Wei. Knowledge Forest: A Novel Model to Organize Knowledge Fragments, Science China (Information Sciences), 2019, Accepted.
Zheng Yan, Jun Liu, Laurence T. Yang, Witold Pedrycz. [Editorial] Data fusion in heterogeneous networks, Information Fusion, 2020, 53, 1-3.
Ming Fan, Xiapu Luo, Jun Liu, Chunyin Nong, Qinghua Zheng, Ting Liu. CTDroid: Leveraging a Corpus of Technical Blogsfor Android Malware Analysis, IEEE Transactions on Reliability, 2019, 69(1): 124-138.
Mengyue Liu, Jun Liu, Yihe Chen, Hao Chen, Meng Wang, Qinghua Zheng.AHNG: Representation Learning on Attributed Heterogeneous Network, Information Fusion, 2019, 50: 221-230.
郑庆华，董博，钱步月，田锋，魏笔凡，张未展，刘均. 智慧教育研究现状与发展趋势, 计算机研究与发展, 2019, 56(1), 209-224.
Meng Wang, Jun Liu, Bifan Wei, Siyu Yao, Hongwei Zeng, Lei Shi. Answering Why-Not Questions on SPARQL Queries. Knowledge and Information Systems. 2019, 58(1): 169-208.
Wenqiang Liu, Jun Liu, Bifan Wei, Yanan Qian, Haimeng Duan, Wei Hu, Xindong Wu. A New Truth Discovery Method for Resolving Object Con?icts over Linked Data with Scale-free Property. Knowledge and Information Systems, 2019, 59(2): 465-495.
Conference Papers
Jie Ma, Jun Liu, Yufei Li, Xin Hu, Yudai Pan, Shen Sun and Qika Lin.Jointly Optimized Neural Coreference Resolution with Mutual Attention. WSDM 2019.
Ruijie Wang , Meng Wang, Jun Liu, Michael Cochez, and Stefan Decker.Leveraging Knowledge Graph Embeddings for Natural Language Question Answering. DASFAA2019.
Zhaotong Guo, Bifan Wei, Jun Liu, Bei Wu. TF-Miner: Topic-specific Facet Mining by Label Propagation. DASFAA2019.
Luguo Xue, Minnan Luo, Zhen Peng, Jundong Li, Yan Chen, Jun Liu, Anomaly Detection in Time-Evolving Attributed Networks. DASFAA2019.
2018:
Journal Papers
Wenqiang Liu, Jun Liu, Mengmeng Wu, Wei Hu, Bifan Wei, Qinghua Zheng. Representation Learning over Multiple Knowledge Graphs for Knowledge Graphs Alignment, Neurocomputing, 2018, 320: 12-24.
Lingyun Song, Jun Liu, Buyue Qian, Mingxuan Sun,et al. A Deep Multi-Modal CNN for Multi-InstanceMulti-Label Image Classification.IEEE Transactions on Image Processing, 2018, 27(12): 6025-6038.
Ming Fan, Jun Liu, Xiapu Luo, Kai Chen, Zhenzhou Tian, Qinghua Zheng, Ting Liu. Android Malware Familial Classification and Representative Sample Selection via Frequent Subgraph Analysis. IEEE Transactions on Information Forensics and Security, 2018, 13(8), 1890-1905 .
Bei Wu, Bifan Wei, Jun Liu, Zhaotong Guo, Yuanhao Zheng, Yihe Chen. Facet Annotation by Extending CNN with a Matching Strategy. Neural Computation. 2018, 30(6), 1647-1672.
Lingling Zhang, Jun Liu, Ninnan Luo, Xiaojun Chang, Qinghua Zheng. Deep Semi-supervised Zero-shot Learning with Maximum Mean Discrepancy. Neural Computation, 2018, 30(5), 1426-1447.
Lingling Zhang, Ninnan Luo, Zhihui Li, Feiping Nie, Huangxiang Zhang, Jun Liu, Qinghua Zheng. Large Scale Robust Semi-supervised Classification. IEEE Transactions on Cybernetics, 2018, 49(3): 907-917.
Zheng Yan, Jun Liu, Laurence T. Yang, Nitesh Chawla. [Editorial]Big Data Fusion in Internet of Things, Information Fusion,2018, 40, 32-33.
Hao Chen, Jun Liu, Yanzhang Lv, Max Haifei Li, Mengyue Liu. Semi-supervised Clues Fusion for Spammer Detection in Sina Weibo. Information Fusion. 2018, 44, 22-32.
Conference Papers
Ming Fan, Xiapu Luo, Jun Liu, Meng Wang, Chunyin Nong, Qinghua Zheng and Ting Liu. Graph Embedding based Familial Analysis of Android Malware using Unsupervised Learning, ICSE2019.
Ming Fan, Xiapu Luo, Jun Liu, Chunyin Nong, Qinghua Zheng and Ting Liu, CTDroid: Leveraging a Corpus of Technical Blogs for Android Malware Analysis. NASAC 2018. （Best Paper Award ）
Lingyun Song, Jun Liu, Buyue Qian, Yihe Chen.Connecting Language to Images: AProgressive Attention-Guided Network for Simultaneous Image Captioning and LanguageGrounding, AAAI2019.
Ruijie Wang, Meng Wang, and Jun Liu.Graph Embedding based Query Construction over Knowledge Graphs.IEEE ICBK2018.（Best Paper Award ）
Ruoqing Ren, Haimeng Duan, Wenqiang Liu and Jun Liu. AUnet: An Unsupervised Method for Answer Reliability Evaluation in Community QA Systems, DMMOOC2018.
Meng Wang, Ruijie Wang, Jun Liu, Yihe Chen, Lei Zhang, Guilin Qi. Towards Empty Answers in SPARQL: Approximating Querying with RDF Embedding, ISWC2018.（Best Student Paper Award Candidate）
Yu Tong, Wang Meng, Lv Yanzhang, Xue Luguo and Liu Jun. Interpretative Topic Categorization via Deep Multiple Instance Learning, IJCNN2018.
Hao Chen, Jun Liu, Yanzhang Lv. A Transfer Metric Learning Method for Spammer Detection.PAKDD2018.
2017:
Journal Papers
Lei Ding, Jun Liu, Tao Qin, Haifei Li. Internet Traffic Classification Based on Expanding Vector of Flow. Computer Networks. 2017, 129, 178-192.
Meng Wang, Weitong Chen, Sen Wang, Jun Liu, Xue Li, Bela Stantic. Answering Why-Not Questions on Semantic Multimedia Queries, Multimedia Tools and Applications, 2017, 77(8), 1-25.
Lingyun Song, Jun Liu, Minnan Luo, Buyue Qian, Kuan Yang.Sparse Relational Topical Coding on Multi-Modal Data, Pattern Recognition, 2017, 72, 368-380.
Xindong Wu, Huanhuan Chen, Jun Liu, Gongqing Wu, Ruqian Lu, and Nanning Zheng. Knowledge Engineering with Big Data (BigKE): A 54-Month, 45-Million RMB, 15-Institution National Grand Project, IEEE Access, 2017, 5(99), 12696-12701.
Ming Fan,Jun Liu,Wei Wang,Haifei Li,Zhenzhou Tian,Ting Liu, DAPASA: Detecting Android Piggybacked Appsthrough Sensitive Subgraph Analysis,IEEE Transactions on Information Forensics and Security,2017, 12(8), 1772-1785.
Yanzhang Lv, Jun Liu, Hao Chen, Jianhong Mi, Mengyue Liu and Qinghua Zheng, Opinioned Post Detection in Sina Weibo, IEEE Access, 2017, 5(1), 7263-7271.
Jun Liu, Zheng Yan, Athanasios V. Vasilakos, and Laurence T. Yang.[Editorial]Data Mining in Cyber, Physical and Social Computing,IEEE SYSTEMS JOURNAL, 2017, 11(1), 194-196
Minnan Luo, Lingling Zhang, Jun Liu and Qinghua Zheng, Distributed Extreme Learning Machine with Alternating Direction Method of Multiplier,Neurocomputing, 2017, 261, 164-170.
Conference Papers
Yuanhao Zheng, Bifan Wei, Jun Liu, Meng Wang, Weitong Chen, Bei Wu and Yihe Chen.Quality Prediction of Newly Proposed Questions in CQA by Leveraging Weakly Supervised Learning,ADMA2017.
Meng Wang, Jiaheng Zhang, Jun Liu, Wei Hu, Sen Wang and Wenqiang Liu.PDD Graph: Bridging Electronic Medical Records and Biomeidcal Knowledge Graphs via Entity Linking,ISWC2017.
Haimeng Duan, Yuanhao Zheng, Lei Shi, Changhong Jin, Hongwei Zeng,and Jun Liu,DKG: An Expanded Knowledge Base for Online Course, DMMOOC2017.
Wenqiang Liu, Jun Liu, Haimeng Duan, Wei Hu and Bifan Wei,Exploiting Source-Object Network to Resolve Object Conflicts in Linked Data,ESWC 2017.
Wenqiang Liu, Jun Liu, Haimeng Duan, Jian Zhang, Wei Hu, and Bifan Wei. [Demo]TruthDiscover: Resolving Object Con?icts on Massive Linked Data, WWW2017.
2009~2016:
Journal Papers
Wenqiang Liu, Jun Liu, Meng Wang, Qinghua Zheng, Wei Zhang, Lingyun Song, Siyu Yao. Faceted Fusion of RDF Data.Information Fusion, 2015, 23, 16-24
Weizhan Zhang, Jun Liu, Chen Liu, Qinghua Zheng, Wei Zhang. Workload Modeling for Virtual Machine-hosted Application. Expert Systems With Applications, 2015, 42(4): 1835-1844.
吴信东, 陈欢欢,刘均,大数据知识工程基础理论及其应用研究, 中国计算机学会通讯, 2016, 12(11), 68-72
Lingyun Song,Minnan Luo,Jun Liu,Lingling Zhang,Haifei Li, Qinghua Zheng,Sparse Multi-Modal Topical Coding for Image Annotation,Neurocomputing,2016, 214, 162-174.
Xindong Wu, Huanhuan Chen, Gong-Qing Wu, Jun Liu, Qinghua Zheng, Xiaofeng He, Aoying Zhou, Zhong-Qiu Zhao, Bifan Wei, Ming Gao, Yang Li, Qiping Zhang, Shichao Zhang, Nanning Zheng, Knowledge Engineering with Big Data, IEEE Intelligent Systems, 2015,30(5),46-55
Jun Liu,Zheng Yan, Laurance T. Yang.[Editorial]Fusion – An aide to data mining in Internet of Things. Information Fusion, 2015, 23, 1-2
Zheng Yan, Jun Liu, Athanasios Vasilakos, Laurance T. Yang, [Editorial] Trustworthy Data Fusion and Mining in Internet of Things. Future Generation Computer Systems, 2015, 49, 45-46
Bifan Wei, Jun Liu, Qinghua Zheng, Wei Zhang, Chenchen Wang, Bei Wu, DF-Miner: Domain-specific Facet Mining by Leveraging the Hyperlink Structure of Wikipedia. Knowledge-Based Systems, 2015, 77, 80-91
Bifan Wei, Jun Liu, Jian Ma, Qinghua Zheng, Wei Zhang, Boqin Feng. Motif-based Hyponym Relation Extraction from Wikipedia Hyperlinks. IEEE Transactions on Knowledge and Data Engineering, 2014, 26(10): 2507-2519.
Bifan Wei, Jun Liu, Qinghua Zheng, Wei Zhang, Xiaoyu Fu, Boqin Feng. A Survey of Faceted Search. Journal of Web Engineering, 2013,12(1-2):41-64.
Jun Liu, Jincheng Wang, Qinghua Zheng, Wei Zhang, Lu Jiang. Topological Analysis of Knowledge Maps. Knowledge-Based Systems, 2012, 36, 260-267.
Jun Liu, Lu Jiang, Zhaohui Wu, Qinghua Zheng and Yanan Qian. Mining Learning-Dependency between Knowledge Units from Text. The VLDB Journal. 2011, 20(3): 335-345
Jun Liu, Lu Jiang, Zhaohui Wu, Qinghua Zheng. Deep Web Adaptive Crawling based on Minimum Executable Pattern. Journal of Intelligent Information Systems, 2011, 36(2): 197-215
Conference Papers
Ming Fan, Jun Liu, Xiapu Luo, Kai Chen, Tianyi Chen, Zhenzhou Tian, Xiaodong Zhang and Ting Liu. Frequent Subgraph based Familial Classification of Android Malware. ISSRE2016. (Best Paper Award)
Siyu Yao, Jun Liu, Meng Wang, Bifan Wei and Xuelu Chen.[Demo]ANNA: Answering Why-Not Questions for SPARQL, ISWC2015
Minnan Luo, Lingling Zhang, Qinghua Zheng, and Jun Liu. Distributed Extreme Learning Machine with Alternating Direction Method of Multiplier, ELM2015.
Meng Wang, Jun Liu, Wenqiang Liu, Qinghua Zheng, Wei Zhang, Lingyun Song, Siyu Yao. Faceted Exploring for Domain Knowledge over Linked Open Data, CIKM2014.
Bifan Wei, Jun Liu, Jian Ma, Qinghua Zheng, Wei Zhang, Boqin Feng. DFT-extractor: A System to Extract Domain-specific Faceted Taxonomies from Wikipedia. WWW2013: 277-280
Bifan Wei, Jun Liu, Jian Ma, Qinghua Zheng, Wei Zhang, Boqin Feng. MOTIF-RE: Motif-based Hypernym/hyponym Relation Extraction from Wikipedia Links.ICONIP2012.
Jun Liu, Lu Jiang, Zhaohui Wu, Qinghua Zheng. Mining Preorder Relation between Knowledge Units from Text. ACM SAC2010

基本信息 - 刘均刘均（Liu Jun）

Email: liukeen(at)xjtu.edu.cn
地址: 西安交通大学彭康楼

获奖与荣誉称号

2020, 中国自动化学会科技进步特等奖（第3贡献人）
2019, 王宽诚育才奖
2018, 陕西省技术发明一等奖（第2贡献人）
2018, 西安交通大学科技工作先进个人
2018, Best Paper Award (NASAC 2018)
2018, Best Paper Award (ICBK 2018)
2018, Best Student Paper Award Candidate (ISWC 2018)
2016, Best Paper Award (The 27th ISSRE)
2014, IEEE Outstanding Service Award (14th IEEE CIT)
2013, Google 奖教金
2010, IBM中国优秀教师奖
2010, 陕西省青年科技奖
2009, 国家教学成果二等奖（第3贡献人）
2008, 教育部新世纪优秀人才
2006, 国家科技进步二等奖（第3贡献人）

基本信息
刘均，西安交通大学计算机系教授，博士生导师；
斯坦福大学、昆士兰大学高级访问****；香港大学、Iowa州立大学访问****；
陕西省天地网技术重点实验室，主任；
西安交通大学跨媒体知识融合与工程应用研究所，所长；
中国通信学会云计算与大数据专委会，委员；
编委：IEEE TNNLS (2020~)；Internet of Things and Cyber-Physical Systems (2021~)
专刊主编：ACM TOMM、Information Fusion、IEEE Systems Journal、Future Generation Computer Systems等；
IEEE 高级会员，CCF 高级会员。
近年来，承担国家重点研发计划项目、国家863目标导向类课题、国家自然科学基金、国家科技支撑计划等课题等10余项课题。授权发明专利16项；获国家科技进步二等奖，国家教学成果二等奖，多项省部级科技进步奖，自动化学会科技进步特等奖；在IJCV、VLDB J、IEEE TKDE、IEEE TIP、ICDE等期刊与国际会议上发表论文百余篇，出版学术专著2部。
研究方向：自然语言理解，计算机视觉，智慧教育。

教育经历
2000年~2004年，西安交通大学电信学院系统工程研究所，工学博士学位。
1995年~1998年，西安交通大学计算机系，获工学硕士学位。
1991年~1995年，西安交通大学计算机系，获工学学士学位。

工作经历
2011年12月至今，西安交通大学电信学院，教授，博士生导师。
2019年7月~8月，德国Karlsruhe Institute of Technology，高级访问****。
2017年8月~9月，美国Stanford University，高级访问****。
2016年7月~8月，澳大利亚The University of Queensland，高级访问****。
2011年7月~8月，美国Iowa State University，访问****。
2005年5~8月，香港大学电子商务技术研究所，访问****。
1998年7月~2011年12月，西安交通大学电信学院，讲师，副教授。

最新动态（2018年以后）
2021:
4月27日，东南大学王萌讲师（毕业博士）回校交流，并作学术报告“多模态知识图谱构建研究进展与挑战”。
4月23日，范铭获得校级优秀博士论文。
2月28日，博士生吴蓓顺利通过博士学位答辩。
1月9日，受邀在陕西师范大学现代教学技术教育部重点实验室的学术年会上作学术报告。
2020:
12月30日，范铭获得陕西省计算机学会优秀博士论文。
12月11日，受邀参加“AI 改变未来”——未来教育 2020 峰会，并作学术报告。
11月6日，由西安交通大学、华中师范大学、北京奥鹏远程教育中心有限公司联合研制的成果“知识森林个性化智能导学技术及其重大应用”获得中国自动化学会科技进步特等奖。（获奖人：郑庆华、杨宗凯、刘均、刘三女牙、魏笔凡、董博等21人)
10月27日，张玲玲与肖乐获得了博后面上基金拟资助。
10月17日，成功举办“新一代AI赋能的智慧教育”论坛。
8月14日，获2019年度“王宽诚”育才奖。
5月24日，博士生张玲玲顺利通过博士学位答辩。
2019:
12月28日，国家重点研发计划项目“教育大数据分析挖掘技术及其智慧教育示范应用”顺利通过中期检查。
12月8日，参加四川大学博士后交叉学科论坛，并做学术报告。
11月16日，牵头研制“知识森林AR交互工具”获2019年中国国际高新技术成果交易会“优秀产品奖”。
9月28日，在武汉参加2019第七届CCF大数据学术会议，并承办“AI+大数据助力智慧教育”论坛。
8月16日，范铭讲师（已毕业博士）获批国家自然科学基金青年基金项目“基于多源软件行为表征的Android恶意软件特征构建与家族识别方法”。
8月16日，东南大学王萌讲师（已毕业博士）获批国家自然科学基金青年基金项目“基于表示学习的知识图谱近似查询方法研究”。
6月19日，范铭讲师（已毕业博士）通过香港理工大学的博士学位答辩，取得双学位。
6月14日，在首都师范大学出席The International Workshop for AI+Teacher Education，并作学术报告。
5月31日，博士生曾宏伟、刘梦月申请的国家留学基金委“建设高水平大学公派研究生”项目获批，将分别赴新加坡南洋理工大学、澳大利亚昆士兰大学访学一年。
5月16日，在北京奥鹏召开国家重点研发计划项目平台构建与示范应用工作专题会议。
4月14日，在西安交通大学召开国家重点研发计划项目进展研讨会。
4月9日，项目"场景感知的知识地图导航移动学习关键技术及其应用"获得2018年陕西省科学技术进步一等奖 (获奖人：郑庆华; 刘均; 董博; 张未展; 魏笔凡; 赵敏; 李国斌; 朱海萍; 杜海鹏; 李睿; 锁志海)
3月29日，博士生宋凌云顺利通过博士学位答辩。
3月26日，在华中师范大学出席“2019中德双边研讨会——人工智能驱动教育技术发展的中德视角”，并作学术报告“Knowledge Forest: A New Tool to OrganizeKnowledge Fragments”。
3月1日，博士生丁磊顺利通过博士学位答辩。
1月12日，博士生范铭顺利通过博士学位答辩。
2018:
12月7日，出席河南省教育厅2018 年“互联网+教育”研讨会，并做特邀报告。
11月27日，学生范铭发表在NASAC会议上的论文CTDroid: Leveraging a Corpus of Technical Blogs for Android Malware Analysis获得Best paper award。
11月9日，学生王瑞杰、王萌发表在ICBK会议上的论文Graph Embedding based Query Construction over Knowledge Graphs获得Best paper award。
11月8日，在华东师范大学出席“数据科学与工程系统学术研讨会”，并做学术报告。
10月17日，国家重点研发计划“云计算和大数据”专项“教育大数据分析挖掘技术及其智慧教育示范应用”项目启动会暨项目实施论证会在西安交通大学召开。
10月6日，学生王萌、王瑞杰发表在ISWC会议上的论文Towards Empty Answers in SPARQL: Approximating Querying with RDF Embedding获得Best Student paper award提名。
9月25日，实验室硕士毕业生蒋路，现Google科学家、Google Cloud AI成员，访问实验室并做学术报告“Towards Deeper Understanding of Image, Video and Language Altogether”。
8月17日，在湖南长沙国防科技大学出席“并行与分布处理前沿技术”高端论坛，并做学术报告“知识森林：聚合碎片化知识的教育知识图谱”。
7月18日，博士生刘文强、王萌顺利通过博士学位答辩。
7月13日，硕士生于通赴巴西里约参加国际会议The International Joint Conference on Neural Networks (IJCNN )。
6月3日，博士生陈浩赴澳大利亚墨尔本参加国际会议The 22nd Pacific-Asia Conference on Knowledge Discovery and Data Mining（PAKDD）。
5月29日，博士生陈浩、吴蓓、张玲玲、吕彦章与硕士生王瑞杰将分别到美国北卡罗来纳大学教堂山分校（UNC）、德国卡尔斯鲁厄理工学院（KIT）、美国卡耐基梅隆大学（CMU）、澳大利亚昆士兰大学（UQ）、德国亚琛工业大学（RWTH Aachen）访学一年。
5月17日，由西安交通大学牵头，国防科技大学、清华大学、华中师范大学、北京奥鹏远程教育中心有限公司等11家单位联合承担的国家重点研发计划“云计算与大数据”重点专项2018年度项目“教育大数据分析挖掘技术及其智慧教育示范应用”获得立项。项目执行期为2018年5月到2021年4月。
2月26日，与李辰教授共同申请的Intel公司产学合作协同育人项目"自然语言理解与机器翻译"（课程建设）获得立项。
2月12日，合作承办了 Information Fusion 的 Special Issue（Data Fusion in Heterogeneous Networks）。

科学研究 - 刘均主持的科研项目
1. 2020.1 ~ 2020.10， 联想横向课题，基于知识森林的教与学系统2. 2020.1 ~ 2020.12，弘成科技合作协同育人项目，数据挖掘3. 2018.5 ~ 2021.4， 国家重点研发计划“云计算和大数据”重点专项，教育大数据分析挖掘技术及其智慧教育示范应用（2018YFB**）4. 2018.1 ~ 2018.12，Intel公司产学合作协同育人项目，自然语言理解与机器翻译5. 2018.1 ~ 2019.12，西安交通大学2017年在线教学改革研究专项项目，基于知识森林的碎片化知识组织与导航学习新模式6. 2017.1 ~ 2020.12， 国家自然科学基金项目，面向开放知识源的知识碎片分面聚合方法研究（**）7. 2016.1 ~ 2017.12， 教育部在线教育研究基金课题，基于大数据挖掘和分析的学习者学习路径优化研究8. 2016.1 ~ 2020.12，国家自然科学基金重点项目（子项目），大规模在线协同学习的机理与方法研究（**）9. 2014.1 ~ 2016.12， 西安交通大学青年教师跟踪支持项目，知识地图导航学习理论与方法10. 2012.1 ~ 2014.12，国家“863”计划子课题，海量web数据内容管理、分析挖掘技术与大型示范应用（2012AA011003）11. 2011.1 ~ 2014.12， 国家自然科学基金项目，知识地图的拓扑与演化特性研究及在e-Learning中的应用（**）12. 2010.1 ~ 2011.12，教育部专项课题，基于知识元的科技论文检索方法研究与应用13. 2010.1 ~ 2012.12，“核高基”国家科技重大专项分课题，基于国产基础软件的数字教育关键技术攻关及示范应用（2010ZX01045-001-005-2）14. 2009.1 ~ 2011.12， 国家自然科学基金项目，面向特定领域文本的知识元及其关联挖掘方法研究（**）15. 2009.1 ~ 2011.12， 教育部“新世纪优秀人才支持计划”项目，面向非结构文本的知识元关联挖掘方法研究（NCET-08-0433）16. 2008.7 ~ 2010.6， 国家“863”计划目标导向课题，面向教育的海量知识资源组织、管理与服务系统（2008AA01Z131）17. 2007.1 ~ 2009.12， 国家科技支撑计划子课题，村镇教育资源远程服务关键技术研究（2006BAJ07B06-2）18. 2005.1 ~ 2007.12，陕西省自然科学基金项目，面向非结构文本的领域知识获取及可计算化研究19. 2002.1 ~ 2003.12， 教育部“行动计划”中央财政专项，计算机教学管理(CMI)示范系统

奖项

没有找到条目。

奖项名称获奖年份奖项类型奖项等级申报部门
中国自动化学会科技进步特等奖：知识森林个性化智能导学技术及其重大应用 2020 社会力量科技奖励其他西安交通大学、华中师范大学、北京奥鹏
场景感知的知识地图导航移动学习关键技术及其应用 2018 省部级科技成果奖一等奖西安交通大学; 北京奥鹏远程教育中心有限公司
税务大数据计算与服务关键技术及其应用 2017 国家科技进步奖二等奖西安交通大学、税友软件集团股份有限公司
国家电子税务大数据分析关键技术及其应用 2013 省部级科技成果奖一等奖税友软件集团股份有限公司、西安交通大学
村镇教育资源配置与远程服务关键技术及应用 2012 省部级科技成果奖二等奖华中师范大学，西安交通大学
国家教学成果二等奖：开放式数字教学资源共享模式探索、平台研究与应用实践 2009 其他二等奖电信学院、网络教育学院
天地网远程教育关键技术、系列产品及其应用 2006 国家科技进步奖二等奖西安交通大学、上海交通大学
现代远程教育支撑平台研究与示范应用 2004 省部级科技成果奖一等奖上海交通大学、西安交通大学
基于IP网的远程教学系统 2003 省部级科技成果奖一等奖西安交通大学

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代表论文
2021:
Book/Book Chapter
郑庆华、刘均、魏笔凡、张玲玲.知识森林：理论、方法与实践, 科学出版社, 2021.
Jun Liu, Lingling Zhang, Bifan Wei, Qinghua Zheng. Virtual Teaching Assistants: Technologies, Applications and Challenges. In: Fang Chen, JianlongZhou (Eds.), Humanity Driven AI: Productivity, Well-being, Sustainability and Partnership, Springer, 2021.
Journal Papers
Qika Lin, Jun Liu, Yudai Pan, Lingling Zhang, Xin Hu, Jie Ma.Rule-Enhanced Iterative Complementation for Knowledge Graph Reasoning, Information Sciences, 2021, Accepted.
Jie Ma, Jun Liu, Yaxian Wang, Junjun Li, and Tongliang Liu. Relation-aware Fine-grained Reasoning Network for Textbook Question Answering, IEEE Transactions on Neural Networks and Learning Systems, 2021, Accepted.
Lingling Zhang, Shaowei Wang, Xiaojun Chang, Jun Liu, Zongyuan Ge, and Qinghua Zheng. Auto-FSL: Searching the Attribute Consistent Network for Few-Shot Learning, IEEE Transactions on Circuits and Systems for Video Technology, 2021, Accepted.
Hongwei Zeng,Zhuo Zhi, Jun Liu, Bifan Wei. Improving Paragraph-level Question Generation with Extended Answer Network and Uncertainty-aware Beam Search. Information Sciences, 2021, Accepted.
Hongwei Zeng, Jun Liu, Meng Wang, Bifan Wei. A Sequence to Sequence Model for Dialogue Generation with Gated Mixture of Topics. Neurocomputing, 2021, Accepted.
Yanxiang Ling, Fei Cai, Xuejun Hu, Jun Liu, Wanyu Chen, and Honghui Chen. Context-Controlled Topic-Aware Neural Response Generation for Open-Domain Dialog Systems. Information Processing & Management, 2021, 58(1): 102392.
Conference Papers
Yanzhang Lyu, Hongzhi Yin, Jun Liu, Mengyue Liu, Huan Liu, Shizhuo Deng. Reliable Recommendation with Review-level Explanations. ICDE 2021.
2020:
Book/Book Chapter
Yao S., Wang R., Sun S., Bu D., Liu J. Joint Embedding Learning of Educational Knowledge Graphs. In: Pinkwart N., Liu S. (eds) Artificial Intelligence Supported Educational Technologies. Advances in Analytics for Learning and Teaching. Springer, 2020.
Journal Papers
Lingyun Song, Jun Liu, Mingxuan Sun, Xuequn Shang.Weakly Supervised Group Mask Network for Object Detection. International Journal of Computer Vision (IJCV), 2020, Accepted.
麻珂欣, 魏笔凡, 马杰, 刘均, 黄毅, 胡珉, 冯俊兰. 知识主题间先序关系挖掘, 大数据, 2020, 已录用.
姚思雨,赵天哲, 王瑞杰. 刘均.规则引导的知识图谱联合嵌入方法, 计算机研究与发展, 2020, 已录用.
Bei Wu; Bifan Wei, Jun Liu, Kewei Wu, Meng Wang, Faceted Text Segmentation via Multi-Task Learning,IEEE Transactions on Neural Networks and Learning Systems, 2020, Accepted.
Xin Hu, Jun Liu, Jie Ma, Yudai Pan, Lingling Zhang, Fine-grained 3D-Attention Prototypes for FewShot Learning, Neural Computation, 2020, 32(9): 1664-1684.
Chenxu Wang, Wei Rao, Wenna Guo, Pinghui Wang, Jun Liu, Xiaohong Guan,Towards Understanding the Instability of Network Embedding, IEEE Transactions on Knowledge and Data Engineering, 2020, Accepted.
Lingling Zhang, Xiaojun Chang, Jun Liu, Minnan Luo, Mahesh Prakash, Alexander Hauptmann, Few-Shot Activity Recognition with Cross-Modal Memory Network, Pattern Recognition, 2020, 108: 107348.
范铭, 刘烃, 刘均, 罗夏朴, 于乐, 管晓宏.安卓恶意软件检测方法综述, 中国科学: 信息科学, 2020, 50(8): 1148-1177.
Conference Papers
Lingling Zhang, Xiaojun Chang, Jun Liu, Sen Wang, Zongyuan Ge, Minnan Luo, Alexander Hauptmann, ZSTAD: Zero-Shot Temporal Activity Detection, CVPR2020.
2019:
Journal Papers
Ruijie Wang; Meng Wang; Jun Liu; Michael Cochez. Structured Query Construction via Knowledge Graph Embedding,Knowledge and Information Systems,2019, Accepted.
Lingling Zhang, Minnan Luo, Jun Liu, Xiaojun Chang, Yi Yang, and Alexander G. Hauptmann. Deep Top-k Ranking for Image-Sentence Matching, IEEE Transaction on Multimedia, 2019, 22(3): 775-785.
Lingling Zhang, Jun Liu, Minnan Luo, Xiaojun Chang, Qinghua Zheng, Alexander G. Hauptmann,Scheduled Sampling for One-Shot Learning via Matching Network, Pattern Recognition, 2019, 96: 106962.
Qinghua Zheng, Jun Liu, Hongwei Zeng, Zhaotong Guo, Bei Wu & Bifan Wei. Knowledge Forest: A Novel Model to Organize Knowledge Fragments, Science China (Information Sciences), 2019, Accepted.
Zheng Yan, Jun Liu, Laurence T. Yang, Witold Pedrycz. [Editorial] Data fusion in heterogeneous networks, Information Fusion, 2020, 53, 1-3.
Ming Fan, Xiapu Luo, Jun Liu, Chunyin Nong, Qinghua Zheng, Ting Liu. CTDroid: Leveraging a Corpus of Technical Blogsfor Android Malware Analysis, IEEE Transactions on Reliability, 2019, 69(1): 124-138.
Mengyue Liu, Jun Liu, Yihe Chen, Hao Chen, Meng Wang, Qinghua Zheng.AHNG: Representation Learning on Attributed Heterogeneous Network, Information Fusion, 2019, 50: 221-230.
郑庆华，董博，钱步月，田锋，魏笔凡，张未展，刘均. 智慧教育研究现状与发展趋势, 计算机研究与发展, 2019, 56(1), 209-224.
Meng Wang, Jun Liu, Bifan Wei, Siyu Yao, Hongwei Zeng, Lei Shi. Answering Why-Not Questions on SPARQL Queries. Knowledge and Information Systems. 2019, 58(1): 169-208.
Wenqiang Liu, Jun Liu, Bifan Wei, Yanan Qian, Haimeng Duan, Wei Hu, Xindong Wu. A New Truth Discovery Method for Resolving Object Con?icts over Linked Data with Scale-free Property. Knowledge and Information Systems, 2019, 59(2): 465-495.
Conference Papers
Jie Ma, Jun Liu, Yufei Li, Xin Hu, Yudai Pan, Shen Sun and Qika Lin.Jointly Optimized Neural Coreference Resolution with Mutual Attention. WSDM 2019.
Ruijie Wang , Meng Wang, Jun Liu, Michael Cochez, and Stefan Decker.Leveraging Knowledge Graph Embeddings for Natural Language Question Answering. DASFAA2019.
Zhaotong Guo, Bifan Wei, Jun Liu, Bei Wu. TF-Miner: Topic-specific Facet Mining by Label Propagation. DASFAA2019.
Luguo Xue, Minnan Luo, Zhen Peng, Jundong Li, Yan Chen, Jun Liu, Anomaly Detection in Time-Evolving Attributed Networks. DASFAA2019.
2018:
Journal Papers
Wenqiang Liu, Jun Liu, Mengmeng Wu, Wei Hu, Bifan Wei, Qinghua Zheng. Representation Learning over Multiple Knowledge Graphs for Knowledge Graphs Alignment, Neurocomputing, 2018, 320: 12-24.
Lingyun Song, Jun Liu, Buyue Qian, Mingxuan Sun,et al. A Deep Multi-Modal CNN for Multi-InstanceMulti-Label Image Classification.IEEE Transactions on Image Processing, 2018, 27(12): 6025-6038.
Ming Fan, Jun Liu, Xiapu Luo, Kai Chen, Zhenzhou Tian, Qinghua Zheng, Ting Liu. Android Malware Familial Classification and Representative Sample Selection via Frequent Subgraph Analysis. IEEE Transactions on Information Forensics and Security, 2018, 13(8), 1890-1905 .
Bei Wu, Bifan Wei, Jun Liu, Zhaotong Guo, Yuanhao Zheng, Yihe Chen. Facet Annotation by Extending CNN with a Matching Strategy. Neural Computation. 2018, 30(6), 1647-1672.
Lingling Zhang, Jun Liu, Ninnan Luo, Xiaojun Chang, Qinghua Zheng. Deep Semi-supervised Zero-shot Learning with Maximum Mean Discrepancy. Neural Computation, 2018, 30(5), 1426-1447.
Lingling Zhang, Ninnan Luo, Zhihui Li, Feiping Nie, Huangxiang Zhang, Jun Liu, Qinghua Zheng. Large Scale Robust Semi-supervised Classification. IEEE Transactions on Cybernetics, 2018, 49(3): 907-917.
Zheng Yan, Jun Liu, Laurence T. Yang, Nitesh Chawla. [Editorial]Big Data Fusion in Internet of Things, Information Fusion,2018, 40, 32-33.
Hao Chen, Jun Liu, Yanzhang Lv, Max Haifei Li, Mengyue Liu. Semi-supervised Clues Fusion for Spammer Detection in Sina Weibo. Information Fusion. 2018, 44, 22-32.
Conference Papers
Ming Fan, Xiapu Luo, Jun Liu, Meng Wang, Chunyin Nong, Qinghua Zheng and Ting Liu. Graph Embedding based Familial Analysis of Android Malware using Unsupervised Learning, ICSE2019.
Ming Fan, Xiapu Luo, Jun Liu, Chunyin Nong, Qinghua Zheng and Ting Liu, CTDroid: Leveraging a Corpus of Technical Blogs for Android Malware Analysis. NASAC 2018. （Best Paper Award ）
Lingyun Song, Jun Liu, Buyue Qian, Yihe Chen.Connecting Language to Images: AProgressive Attention-Guided Network for Simultaneous Image Captioning and LanguageGrounding, AAAI2019.
Ruijie Wang, Meng Wang, and Jun Liu.Graph Embedding based Query Construction over Knowledge Graphs.IEEE ICBK2018.（Best Paper Award ）
Ruoqing Ren, Haimeng Duan, Wenqiang Liu and Jun Liu. AUnet: An Unsupervised Method for Answer Reliability Evaluation in Community QA Systems, DMMOOC2018.
Meng Wang, Ruijie Wang, Jun Liu, Yihe Chen, Lei Zhang, Guilin Qi. Towards Empty Answers in SPARQL: Approximating Querying with RDF Embedding, ISWC2018.（Best Student Paper Award Candidate）
Yu Tong, Wang Meng, Lv Yanzhang, Xue Luguo and Liu Jun. Interpretative Topic Categorization via Deep Multiple Instance Learning, IJCNN2018.
Hao Chen, Jun Liu, Yanzhang Lv. A Transfer Metric Learning Method for Spammer Detection.PAKDD2018.
2017:
Journal Papers
Lei Ding, Jun Liu, Tao Qin, Haifei Li. Internet Traffic Classification Based on Expanding Vector of Flow. Computer Networks. 2017, 129, 178-192.
Meng Wang, Weitong Chen, Sen Wang, Jun Liu, Xue Li, Bela Stantic. Answering Why-Not Questions on Semantic Multimedia Queries, Multimedia Tools and Applications, 2017, 77(8), 1-25.
Lingyun Song, Jun Liu, Minnan Luo, Buyue Qian, Kuan Yang.Sparse Relational Topical Coding on Multi-Modal Data, Pattern Recognition, 2017, 72, 368-380.
Xindong Wu, Huanhuan Chen, Jun Liu, Gongqing Wu, Ruqian Lu, and Nanning Zheng. Knowledge Engineering with Big Data (BigKE): A 54-Month, 45-Million RMB, 15-Institution National Grand Project, IEEE Access, 2017, 5(99), 12696-12701.
Ming Fan,Jun Liu,Wei Wang,Haifei Li,Zhenzhou Tian,Ting Liu, DAPASA: Detecting Android Piggybacked Appsthrough Sensitive Subgraph Analysis,IEEE Transactions on Information Forensics and Security,2017, 12(8), 1772-1785.
Yanzhang Lv, Jun Liu, Hao Chen, Jianhong Mi, Mengyue Liu and Qinghua Zheng, Opinioned Post Detection in Sina Weibo, IEEE Access, 2017, 5(1), 7263-7271.
Jun Liu, Zheng Yan, Athanasios V. Vasilakos, and Laurence T. Yang.[Editorial]Data Mining in Cyber, Physical and Social Computing,IEEE SYSTEMS JOURNAL, 2017, 11(1), 194-196
Minnan Luo, Lingling Zhang, Jun Liu and Qinghua Zheng, Distributed Extreme Learning Machine with Alternating Direction Method of Multiplier,Neurocomputing, 2017, 261, 164-170.
Conference Papers
Yuanhao Zheng, Bifan Wei, Jun Liu, Meng Wang, Weitong Chen, Bei Wu and Yihe Chen.Quality Prediction of Newly Proposed Questions in CQA by Leveraging Weakly Supervised Learning,ADMA2017.
Meng Wang, Jiaheng Zhang, Jun Liu, Wei Hu, Sen Wang and Wenqiang Liu.PDD Graph: Bridging Electronic Medical Records and Biomeidcal Knowledge Graphs via Entity Linking,ISWC2017.
Haimeng Duan, Yuanhao Zheng, Lei Shi, Changhong Jin, Hongwei Zeng,and Jun Liu,DKG: An Expanded Knowledge Base for Online Course, DMMOOC2017.
Wenqiang Liu, Jun Liu, Haimeng Duan, Wei Hu and Bifan Wei,Exploiting Source-Object Network to Resolve Object Conflicts in Linked Data,ESWC 2017.
Wenqiang Liu, Jun Liu, Haimeng Duan, Jian Zhang, Wei Hu, and Bifan Wei. [Demo]TruthDiscover: Resolving Object Con?icts on Massive Linked Data, WWW2017.
2009~2016:
Journal Papers
Wenqiang Liu, Jun Liu, Meng Wang, Qinghua Zheng, Wei Zhang, Lingyun Song, Siyu Yao. Faceted Fusion of RDF Data.Information Fusion, 2015, 23, 16-24
Weizhan Zhang, Jun Liu, Chen Liu, Qinghua Zheng, Wei Zhang. Workload Modeling for Virtual Machine-hosted Application. Expert Systems With Applications, 2015, 42(4): 1835-1844.
吴信东, 陈欢欢,刘均,大数据知识工程基础理论及其应用研究, 中国计算机学会通讯, 2016, 12(11), 68-72
Lingyun Song,Minnan Luo,Jun Liu,Lingling Zhang,Haifei Li, Qinghua Zheng,Sparse Multi-Modal Topical Coding for Image Annotation,Neurocomputing,2016, 214, 162-174.
Xindong Wu, Huanhuan Chen, Gong-Qing Wu, Jun Liu, Qinghua Zheng, Xiaofeng He, Aoying Zhou, Zhong-Qiu Zhao, Bifan Wei, Ming Gao, Yang Li, Qiping Zhang, Shichao Zhang, Nanning Zheng, Knowledge Engineering with Big Data, IEEE Intelligent Systems, 2015,30(5),46-55
Jun Liu,Zheng Yan, Laurance T. Yang.[Editorial]Fusion – An aide to data mining in Internet of Things. Information Fusion, 2015, 23, 1-2
Zheng Yan, Jun Liu, Athanasios Vasilakos, Laurance T. Yang, [Editorial] Trustworthy Data Fusion and Mining in Internet of Things. Future Generation Computer Systems, 2015, 49, 45-46
Bifan Wei, Jun Liu, Qinghua Zheng, Wei Zhang, Chenchen Wang, Bei Wu, DF-Miner: Domain-specific Facet Mining by Leveraging the Hyperlink Structure of Wikipedia. Knowledge-Based Systems, 2015, 77, 80-91
Bifan Wei, Jun Liu, Jian Ma, Qinghua Zheng, Wei Zhang, Boqin Feng. Motif-based Hyponym Relation Extraction from Wikipedia Hyperlinks. IEEE Transactions on Knowledge and Data Engineering, 2014, 26(10): 2507-2519.
Bifan Wei, Jun Liu, Qinghua Zheng, Wei Zhang, Xiaoyu Fu, Boqin Feng. A Survey of Faceted Search. Journal of Web Engineering, 2013,12(1-2):41-64.
Jun Liu, Jincheng Wang, Qinghua Zheng, Wei Zhang, Lu Jiang. Topological Analysis of Knowledge Maps. Knowledge-Based Systems, 2012, 36, 260-267.
Jun Liu, Lu Jiang, Zhaohui Wu, Qinghua Zheng and Yanan Qian. Mining Learning-Dependency between Knowledge Units from Text. The VLDB Journal. 2011, 20(3): 335-345
Jun Liu, Lu Jiang, Zhaohui Wu, Qinghua Zheng. Deep Web Adaptive Crawling based on Minimum Executable Pattern. Journal of Intelligent Information Systems, 2011, 36(2): 197-215
Conference Papers
Ming Fan, Jun Liu, Xiapu Luo, Kai Chen, Tianyi Chen, Zhenzhou Tian, Xiaodong Zhang and Ting Liu. Frequent Subgraph based Familial Classification of Android Malware. ISSRE2016. (Best Paper Award)
Siyu Yao, Jun Liu, Meng Wang, Bifan Wei and Xuelu Chen.[Demo]ANNA: Answering Why-Not Questions for SPARQL, ISWC2015
Minnan Luo, Lingling Zhang, Qinghua Zheng, and Jun Liu. Distributed Extreme Learning Machine with Alternating Direction Method of Multiplier, ELM2015.
Meng Wang, Jun Liu, Wenqiang Liu, Qinghua Zheng, Wei Zhang, Lingyun Song, Siyu Yao. Faceted Exploring for Domain Knowledge over Linked Open Data, CIKM2014.
Bifan Wei, Jun Liu, Jian Ma, Qinghua Zheng, Wei Zhang, Boqin Feng. DFT-extractor: A System to Extract Domain-specific Faceted Taxonomies from Wikipedia. WWW2013: 277-280
Bifan Wei, Jun Liu, Jian Ma, Qinghua Zheng, Wei Zhang, Boqin Feng. MOTIF-RE: Motif-based Hypernym/hyponym Relation Extraction from Wikipedia Links.ICONIP2012.
Jun Liu, Lu Jiang, Zhaohui Wu, Qinghua Zheng. Mining Preorder Relation between Knowledge Units from Text. ACM SAC2010

教学工作 - 刘均讲授课程
1. 本科生课程：《数据仓库与数据挖掘》，学时数： 32。
课程简介：数据挖掘旨在研究如何从大量数据中挖掘未知的、有价值的、新知识或规律。该课程的教学内容主要包括：（1）数据挖掘的基本概念，功能，处理过程及应用领域；（2）数据预处理，包括数据样本的缺失处理、数据清理和数据归约；（3）针对不同的挖掘任务，介绍各种算法，包括概念描述、关联规则分析、序列模式、分类、聚类等；（4）复杂类型数据的挖掘，重点介绍文本、WEB数据特点，介绍其特有的挖掘算法；（5）数据挖掘的应用和发展趋势。
2. 本科生课程：《自然语言理解与机器翻译》（计算机与人工智能试验班），学时数： 32。
课程简介：自然语言理解与机器翻译（Natural Language Understanding & Machine Translation，NLU&MT）是人工智能领域的前沿技术课程。主要目的包括：（1）使学生掌握NLU方向持久性的科学原理以及最新的模型与方法，了解该方向面临的挑战与发展趋势。（2）利用开放数据集与Intel提供的计算平台开展一系列NLU实验，提高学生的科研能力和理论联系实践的能力。（3）使学生初步具备利用NLU知识解决实际问题的能力。

研究生