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.
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.
Chao Zhang, Yu Zheng, Xiuli Ma, and Jiawei Han, Assembler: Efficient Discovery of Spatial Co-evolving Patterns in Massive Geo-sensory Data, in KDD 2015, August 2015.
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- Data Science at Microsoft
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