WAMDM means " Web And Mobile Data Management", Which is Professor Xiaofeng Meng's research lab and is affiliated with the Key Laboratory for Data Engineering and Knowledge Engineering MOE and the Department of Computer Science, School of Information, Renmin University of China.
Since the beginning of the new century, a problem commonly faced by the database field is, after the traditional database technology matures, where should the database research go? Relying on my own judgment on the technological trends at that time, I set my research goals to solve the challenging problems arising from the cross-combination of database technology, Web computing and mobile computing, namely the management of diversely structured Web data, the management of semi-structured XML data, and Data management issues in the mobile environment, and established the "Web and Mobile Data Management Laboratory (Web and Mobile Data Management)", dedicated to research in this area, and achieved some well-known research results at home and abroad. I summarize this stage of research as Innovation Data Management Research 1.0. Since 2011 is the beginning of another decade, we are thinking about the research layout of the laboratory for the next decade. It is not difficult to find that the transformation of database technology (in fact, any information technology is the same) mainly comes from three driving forces, namely: computing model, hardware technology, and continuous innovation of application model. Based on the needs of the three driving forces, we summarize the research for the next decade as Innovative Data Management Research 2.0, which specifically includes the following research directions:
l Research on flash memory database system. It comes from the driving force of hardware technology change, and its research goal is to study a new flash memory database management technology based on the characteristics of flash memory hardware, flexible application modes and the shortcomings of traditional database technology;
l Research on cloud database system. It comes from the driving force of computing model change, and its research goal is to realize a cloud database system with flexible configuration, high availability, high fault tolerance, scalability and high performance;
l Web and social computing research. It comes from the driving force of application model change, and its research goal is to introduce social computing methods into Web data management, build large-scale knowledge graphs, and solve the application and credibility of Web information;
l Privacy protection research. It comes from the driving force of the application mode change, that is, the demand for Mobile Web is becoming increasingly urgent. Its research goals are to solve key issues such as mobile search and privacy protection. The main research contents include federated learning, differential privacy, blockchain and data transparency, fairness, etc. ;
l Research on big data analysis. It comes from the driving force of application mode change, and its research goal is to introduce data analysis technology into real scenarios, such as astronomical big data analysis.
The site contains information on the projects that are currently in progress and the people in the group. You can also find information on the weekly seminar and annual report. In addition, this site hosts the following webpages:
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· Qingqing Ye, Haibo Hu, Ninghui Li, Xiaofeng Meng, Huadi Zheng, Haotian Yan: Beyond Value Perturbation: Local Differential Privacy in the Temporal Setting. INFOCOM : 1-10(2021)
· Junxu Liu, Jian Lou, Li Xiong, Jinfei Liu and Xiaofeng Meng: Projected Federated Averaging with Heterogeneous Differential Privacy. Proc. VLDB Endow. 15(4): 828–840(2021).
· Changyin Luo, Tangpeng Dan, Yanhong Li, Xiaofeng Meng, Guohui Li: Why-not questions about spatial temporal top-k trajectory similarity search. Knowl. Based Syst. 231: 107407 (2021)
· 张祎,孟小峰.InterTris：三元交互的领域知识图谱表示学习[J].计算机学报,2021,44(08):1535-1548.
· 孟小峰, 刘立新. 基于区块链的数据透明化：问题与挑战[J]. 计算机研究与发展, 2021, 第58卷(2):237-252.
· 朱敏杰,叶青青,孟小峰,杨鑫.基于权限的移动应用程序隐私风险量化[J].中国科学:信息科学,2021,51(07):1100-1115
· 孟小峰. 科学数据智能:人工智能在科学发现中的机遇与挑战[J]. 中国科学基金,2021,35(3):419-425.
· 王雷霞,孟小峰.ESA:一种新型的隐私保护框架[J].计算机研究与发展,2022,59(01):144-171.(2021年在线出版)
· Gang Pan, Hui Lin, Xiaofeng Meng, Yunjun Gao, Yong Li, Qingfeng Guan, Zhiming Ding: Spatial Data and Intelligence - Second International Conference, SpatialDI 2021, Hangzhou, China, April 22-24, 2021, Proceedings. Lecture Notes in Computer Science 12753, Springer 2021, ISBN 978-3-030-85461-4.
· Xiaofeng Meng, Xing Xie, Yang Yue, Zhiming Ding:Spatial Data and Intelligence - First International Conference, SpatialDI 2020, Virtual Event, May 8-9, 2020, Proceedings. Lecture Notes in Computer Science 12567, Springer 2021, ISBN 978-3-030-69872-0.
· Xiaofeng Meng, Fusheng Wang, Chang-Tien Lu, Yan Huang, Shashi Shekhar, Xing Xie:
· SIGSPATIAL '21: 29th International Conference on Advances in Geographic Information Systems, Virtual Event / Beijing, China, November 2-5, 2021. ACM 2021, ISBN 978-1-4503-8664-7.
· Shuo Wang, Aishan Maoliniyazi, Xinle Wu, and Xiaofeng Meng. Emo2Vec: Learning emotional embeddings via multi-emotion category[J]. ACM Transactions on Internet Technology (TOIT), 2020, 20(2): 1-17.
· Wu X, Wang L, Wang S, et al. A Unified Adversarial Learning Framework for Semi-supervised Multi-target Domain Adaptation[C], DASFAA 2020.
· Chen Yang, Yongjie Du, Zhihui Du, Xiaofeng Meng:Micro Analysis to Enable Energy-Efficient Database Systems. EDBT 2020: 61-72
· Q. Ye, H. Hu, M. H. Au, X. Meng, X. Xiao. LF-GDPR: Graph Metric Estimation with Local Differential Privacy. IEEE Transactions on Knowledge and Data Engineering (TKDE)
· Q. Ye, H. Hu, M. H. Au, X. Meng, X. Xiao. Towards Locally Differentially Private Generic Graph Metric Estimation. Proc. of the 36th IEEE International Conference on Data Engineering (ICDE’20), Dallas, USA, Apr. 2020, pp 1922-1925.
· Minjie Zhu , Qingqing Ye , Xiaofeng Meng , Xin Yang . Permission-based mobile application privacy risk quantification[J]. Science in China: Information Science, accepted
· Xiaofeng Meng , Lixin Liu . Blockchain and Data Governance[J]. National Science Foundation of China, 2020,34(1):12-17.
· Xiaofeng Meng ,Lixin Liu . Blockchain-based data transparency: problems and challenges[J]. Computer Research and Development, accepted
· Xiaofeng Meng .Study on Several Governance Models of Cracking Data Monopoly[J].People's Forum,2020(27):58-61.
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