Finding patterns and insights in data
Our work in this area focuses on solving key problems in database architecture and information management. Our current areas of focus are infrastructure for large-scale database systems; reducing the total cost of ownership of information management; enabling flexible ways to query, browse, and organize rich data sets containing both structured and unstructured data; and the management of database schemas and mappings.
Yanjie Fu, Yong Ge, Yu Zheng, Yao, Yanchi Liu, Hui Xiong, and Nicholas Jing Yuan, Sparse Real Estate Ranking with Online User Reviews and Offline Moving Behaviors, in ICDM 2014, IEEE – Institute of Electrical and Electronics Engineers, December 2015.
Yu Zheng, Trajectory Data Mining: An Overview, in ACM Transaction on Intelligent Systems and Technology, ACM – Association for Computing Machinery, September 2015.
Rui Ding, Qiang Wang, Yingnong Dang, Qiang Fu, Haidong Zhang, and Dongmei Zhang, YADING: Fast Clustering of Large-Scale Time Series Data, VLDB – Very Large Data Bases, September 2015.
Mohan Yang, bolin ding, surajit chaudhuri, and kaushik chakrabarti, Finding Patterns in a Knowledge Base using Keywords to Compose Table Answers, VLDB – Very Large Data Bases, August 2015.
- Microsoft Academic Graph
- ATL Cairo GPSP - Projects Ideas
- Urban Air
- Crowdsourcing and Human Computation
- Rethinking Eventual Consistency
- SQLVM: Performance Isolation in Multi-Tenant Relational Database-as-a-Service
- Hyder, a transactional indexed-record manager for shared flash
- Tools for Software Engineers
- Academic Search
- LiveLabs: Testing the usefulness of mobile data
29 May 2015
- Picture this: Microsoft Research project can interpret, caption photos
28 May 2015
- Chain reaction of collaboration improves location-based services privacy
28 May 2015
- Always Encrypted: SQL Server 2016 includes new advances that keep data safer
27 May 2015