Computer Science Carnegie Mellon University / Northwestern University / /
IndustryTerm
multiresolution algorithm / then base-case-search / data mining applications / multiresolution search / approximate algorithms / naive search / over-the-counter retail data / spatial data mining problems / base-case-search / retail sales / medical imaging / real-world epidemiological applications / spatial data mining / epidemiological applications / search-outerregions procedure / elegant solution / recursive depth-first search / search procedure / approximate solution / data mining literature / data mining / multiresolution partitioning algorithm / cluster detection algorithms / algorithmic and statistical tools / multiresolution search procedure / approximate algorithm / exhaustive search / overlap-search / then search-outer-regions / /
Organization
National Science Foundation / Significant Spatial Clusters Daniel B. Neill Andrew W. Moore Department / MIT / Emergency Department / Northwestern University / PC SS / Carnegie Mellon University / /
Person
B. Neill Andrew / Case / Andrew W. Moore / Daniel B. Neill / / /
Position
editor / Data Mining General / /
ProvinceOrState
South Carolina / New York / Massachusetts / Washington / /
Rapid Detection of Significant Spatial Clusters Daniel B. Neill Andrew W. Moore Department of Computer Science