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 ~)
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

7/2019–8/2019    Senior Visiting Fellow, Karlsruhe Institute of Technology (KIT), Germany

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

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 (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, CV, e-learning

Selected Publications

2021:

  • Yanzhang Lyu, Hongzhi Yin, Jun Liu, Mengyue Liu, Huan Liu, Shizhuo Deng. Reliable Recommendation with Review-level Explanations. ICDE 2021.
  • 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.

2020:

  • 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.
  • 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.
  • 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.
  • Lingling Zhang, Xiaojun Chang, Jun Liu, Sen Wang, Zongyuan Ge, Minnan Luo, Alexander Hauptmann, ZSTAD: Zero-Shot Temporal Activity Detection, CVPR2020.
  • 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.

2019:

  • 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. 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 Blogs for 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.
  • 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.
  • 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 Conflicts over Linked Data with Scale-free Property. Knowledge and Information Systems, 2019, 59(2): 465-495.

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. 
  • 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. 
  • 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.
  • Ruijie Wang, Meng Wang, and Jun Liu. Graph Embedding based Query Construction over Knowledge Graphs. IEEE ICBK2018. （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, 2018, 27(12): 6025-6038.
  • 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.
  • 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.

2017: 

  • 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: 

  • 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.
  • 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)
  • 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, ISWC2015
  • Minnan Luo, Lingling Zhang, Qinghua Zheng, and Jun Liu. Distributed Extreme Learning Machine with Alternating Direction Method of Multiplier, ELM2015.
  • 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
  • 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. 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.
  • 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  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. ACM SAC2010