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» Informative sampling for large unbalanced data sets
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232
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SIGMOD
2009
ACM
175views Database» more  SIGMOD 2009»
16 years 4 months ago
Ranking distributed probabilistic data
Ranking queries are essential tools to process large amounts of probabilistic data that encode exponentially many possible deterministic instances. In many applications where unce...
Feifei Li, Ke Yi, Jeffrey Jestes
137
Voted
ESA
2010
Springer
183views Algorithms» more  ESA 2010»
15 years 5 months ago
Spatio-temporal Range Searching over Compressed Kinetic Sensor Data
As sensor networks increase in size and number, efficient techniques are required to process the very large data sets that they generate. Frequently, sensor networks monitor object...
Sorelle A. Friedler, David M. Mount
CVPR
2000
IEEE
16 years 5 months ago
3-D Model Construction Using Range and Image Data
This paper deals with the automated creation of geometric and photometric correct 3-D models of the world. Those models can be used for virtual reality, tele? presence, digital ci...
Ioannis Stamos, Peter K. Allen
IDEAS
2008
IEEE
105views Database» more  IDEAS 2008»
15 years 10 months ago
Pruning attribute values from data cubes with diamond dicing
Data stored in a data warehouse are inherently multidimensional, but most data-pruning techniques (such as iceberg and top-k queries) are unidimensional. However, analysts need to...
Hazel Webb, Owen Kaser, Daniel Lemire
TOIS
2002
97views more  TOIS 2002»
15 years 3 months ago
Burst tries: a fast, efficient data structure for string keys
Many applications depend on efficient management of large sets of distinct strings in memory. For example, during index construction for text databases a record is held for each d...
Steffen Heinz, Justin Zobel, Hugh E. Williams