Processing and extracting meaningful knowledge from count data is an important problem in data mining. The volume of data is increasing dramatically as the data is generated by da...
As the scope of personal data grows, it becomes increasingly difficult to find what we need when we need it. Desktop search tools provide a potential answer, but most existing too...
Sam Shah, Craig A. N. Soules, Gregory R. Ganger, B...
Database queries are often exploratory and users often find their queries return too many answers, many of them irrelevant. Existing work either categorizes or ranks the results t...
We present STAR, a self-tuning algorithm that adaptively sets numeric precision constraints to accurately and efficiently answer continuous aggregate queries over distributed data...
Navendu Jain, Michael Dahlin, Yin Zhang, Dmitry Ki...
Abstract. This text is an informal review of several randomized algorithms that have appeared over the past two decades and have proved instrumental in extracting efficiently quant...