We consider the task of suggesting related queries to users after they issue their initial query to a web search engine. We propose a machine learning approach to learn the probab...
Many database applications require the analysis and processing of data streams. In such systems, huge amounts of data arrive rapidly and their values change over time. The variati...
Lv-an Tang, Bin Cui, Hongyan Li, Gaoshan Miao, Don...
A key method for privacy preserving data mining is that of randomization. Unlike k-anonymity, this technique does not include public information in the underlying assumptions. In ...
We describe METRICS, a system to recover design productivity via new infrastructure for design process optimization. METRICS seeks to treat system design and implementation as a s...
Stephen Fenstermaker, David George, Andrew B. Kahn...
We consider the problem of finding duplicates in data streams. Duplicate detection in data streams is utilized in various applications including fraud detection. We develop a solu...