西安交通大学教师个人主页 刘 均

   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

  Guest Editor

           Information Fusion (SI: Data Fusion in Heterogeneous Networks, 2018-2019)

           Information Fusion (SI: Big Data Fusion in Internet of Things, 2016-2017)

           ACM TOMM (SI: Trust Management for Multimedia Big Data, 2015-1016)

           IEEE Systems Journal (SI: Data Mining in Cyber, Physical and Social Computing, 2014-2015)

            Future Generation Computer Systems (SI: Trustworthy Data Fusion and Mining in Internet of Things, 2014)

           Information Fusion (SI: Fusion – An aide to data mining in Internet of Things, 2013-2014)

   IEEE Member, ACM Member, CCF Senior Member

12/2011–present  Professor, Department of Computer Science and Technology, XJTU, China

8/2017–9/2017    Senior Visiting Fellow, Stanford University, USA

7/2016–8/2016    Senior Visiting Fellow, Queensland University, Australia

7/2011–8/2011    Visiting Scholar, Iowa State University, USA

7/1998–12/2011   Lecturer, Assoc. Prof., Department of Computer Science and Technology, XJTU, China

5/2005–8/2005    Visiting Scholar, University of Hong Kong, Hong Kong, China

9/1999–3/2004    Ph.D., Systems Engineering, XJTU, China

9/1995–7/1998    M.Eng., Computer Architecture, XJTU, China 

9/1991–7/1995    B.Eng., Computer Science and Technology, Xi’an Jiaotong University (XJTU), China

5/2018–4/2021   Educational Data Analysis and Mining for Smart Education,

                            funded by the National Key Research and Development Program of China (2018YFB1004500)

1/2017–12/2020  Faceted Fusion of Knowledge Fragments from Open Knowledge Sources,

                            funded by the National Natural Science Foundation of China (61672419)

1/2016–12/2020  Massive Online Collaborative Learning,

                            funded by the National Natural Science Foundation of China (61532004)

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 (60803079)

1/2012–12/2015  Topology and evolution characteristics of knowledge map,     
                         funded by the National Natural Science Foundation of China (61173112)

Research Interests: NLP, e-learning

2019:

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, Accepted.

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 Blogs for Android Malware Analysis, IEEE Transactions on Reliability, 2019, Accepted. (CCF A)

Mengyue Liu, Jun Liu, Yihe Chen, Hao Chen, Meng Wang, Qinghua Zheng. AHNG: Representation Learning on Attributed Heterogeneous Network,  Information Fusion, 2019,  Accepted.

Ruijie Wang , Meng Wang, Jun Liu, Michael Cochez, and Stefan Decker. Leveraging Knowledge Graph Embeddings for Natural Language Question Answering. DASFAA2019. Accepted. (CCF B)

Zhaotong Guo, Bifan Wei, Jun Liu, Bei Wu. TF-Miner: Topic-specific Facet Mining by Label Propagation. DASFAA2019. Accepted. (CCF B)

Luguo Xue, Minnan Luo, Zhen Peng, Jundong Li, Yan Chen, Jun Liu, Anomaly Detection in Time-Evolving Attributed Networks. DASFAA2019. Accepted. (CCF B)

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.

2018:

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, Accepted. ( CCF A)

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: A Progressive Attention-Guided Network for Simultaneous Image Captioning and Language Grounding, AAAI2019, Accepted.  ( CCF A)

Wenqiang Liu, Jun Liu, Mengmeng Wu, Wei Hu, Bifan Wei, Qinghua Zheng. Representation Learning over Multiple Knowledge Graphs for Knowledge Graphs Alignment, Neurocomputing, Accepted.

Ruijie Wang, Meng Wang, and Jun Liu. Graph Embedding based Query Construction over Knowledge Graphs. IEEE International Conference on Big Knowledge. Singapore, 2018. （Best Paper Award ）

Lingyun Song, Jun Liu, Buyue Qian, Mingxuan Sun,et al. A Deep Multi-Modal CNN for Multi-Instance Multi-Label Image Classification. IEEE Transactions on Image Processing. Accepted.

Ruoqing Ren, Haimeng Duan, Wenqiang Liu and Jun Liu. AUnet: An Unsupervised Method for Answer Reliability Evaluation in Community QA Systems. The Second International Workshop on Data Management and Mining on MOOCs, Macau, China, 2018.

Meng Wang, Ruijie Wang, Jun Liu, Yihe Chen, Lei Zhang, Guilin Qi. Towards Empty Answers in SPARQL: Approximating Querying with RDF Embedding. The 17th International Semantic Web Conference (ISWC). Monterey, USA, 2018.（Best Student Paper Award Candidate）

Yu Tong, Wang Meng, Lv Yanzhang, Xue Luguo and Liu Jun. Interpretative Topic Categorization via Deep Multiple Instance Learning. International Joint Conference on Neural Networks (IJCNN). Rio de Janeiro, Brazil, 2018. 

Hao Chen, Jun Liu, Yanzhang Lv. A Transfer Metric Learning Method for Spammer Detection. In Proceedings of the 22nd Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), Melbourne, Australia, 2018.

Wenqiang Liu, Jun Liu, Bifan Wei, Yanan Qian, Haimeng Duan, Wei Hu, Xindong Wu. A New Truth Discovery Method for Resolving Object Conflicts over Linked Data with Scale-free Property. Knowledge and Information Systems. Accepted.

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. Accepted.

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(IF: 5.667). 2018, 44, 22-32.

2017: 

Meng Wang, Jun Liu, Bifan Wei, Siyu Yao, Hongwei Zeng, Lei Shi. Answering Why-Not Questions on SPARQL Queries. Knowledge and Information Systems. Accepted. 

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.

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.

Lingyun Song, Jun Liu, Minnan Luo, Buyue Qian, Kuan Yang.Sparse Relational Topical Coding on Multi-Modal Data, Pattern Recognition., 2017, 72, 368-380.

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. 

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 Apps through 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.

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 Conflicts on Massive Linked Data, WWW2017.

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. 

2009~2016: 

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. The 27th International Symposium on Software Reliability Engineering (ISSRE) , Ottawa, Canada, 2016. (Best Paper Award)

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.

Siyu Yao, Jun Liu, Meng Wang, Bifan Wei and Xuelu Chen.  [Demo]ANNA: Answering Why-Not Questions for SPARQL. The 14th International Semantic Web Conference(ISWC), Bethlehem, PA, USA, 2015 

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

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.

Meng Wang, Jun Liu, Wenqiang Liu, Qinghua Zheng, Wei Zhang, Lingyun Song, Siyu Yao. Faceted Exploring for Domain Knowledge over Linked Open Data. The 23rd ACM International Conference on Information and Knowledge Management (CIKM) , November 2014, Shanghai, China

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, 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, 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, Sha Sha, Qinghua Zheng, Wei Zhang. Ranking the Difficulty Level of the Knowledge Units Based on Learning Dependency. International Journal of Distance Education Technologies, 2012.

Bifan Wei, Jun Liu, Jian Ma, Qinghua Zheng, Wei Zhang, Boqin Feng. MOTIF-RE: Motif-based Hypernym/hyponym Relation Extraction from Wikipedia Links. The 19th International Conference on Neural Information Processing (ICONIP ), Doha, Qatar, 2012.

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

Jun Liu,  Lu Jiang, Zhaohui Wu, Qinghua Zheng. Mining Preorder Relation between Knowledge Units from Text. In 25th ACM /SIGAPP Symposium on Applied Computing(SAC 2010). Sierre, Switzerland, 2010

Jun Liu,  Zhaohui Wu, Lu Jiang, Qinghua Zheng, Xiao Liu. Crawling Deep Web Content Through Query Forms. In 5th international Conference on Web Information Systems and Technologies (WEBIST2009), Lisbon Portugal, 2009

Lu Jiang, Jun Liu, Zhaohui Wu, Qinghua Zheng. ETM Toolkit A Development Tool Based On Extended Topic Map. In 13th international Conference on Computer Supported Cooperative Work in Design CSCWD2009, Santiago, Chile, 2009