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» Evaluating the spatial indexing of dense point sets
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ICDM
2003
IEEE
138views Data Mining» more  ICDM 2003»
13 years 10 months ago
PixelMaps: A New Visual Data Mining Approach for Analyzing Large Spatial Data Sets
PixelMaps are a new pixel-oriented visual data mining technique for large spatial datasets. They combine kerneldensity-based clustering with pixel-oriented displays to emphasize c...
Daniel A. Keim, Christian Panse, Mike Sips, Stephe...
ECCV
2008
Springer
14 years 6 months ago
An Efficient Dense and Scale-Invariant Spatio-Temporal Interest Point Detector
Over the years, several spatio-temporal interest point detectors have been proposed. While some detectors can only extract a sparse set of scaleinvariant features, others allow for...
Geert Willems, Tinne Tuytelaars, Luc J. Van Gool
ICDE
1998
IEEE
142views Database» more  ICDE 1998»
14 years 6 months ago
High Dimensional Similarity Joins: Algorithms and Performance Evaluation
Current data repositories include a variety of data types, including audio, images and time series. State of the art techniques for indexing such data and doing query processing r...
Nick Koudas, Kenneth C. Sevcik
SIGMOD
1989
ACM
94views Database» more  SIGMOD 1989»
13 years 8 months ago
Redundancy in Spatial Databases
Spatial objects other than points and boxes can be stored in spatial indexes, but the techniques usually require the use of approximations that can be arbitrarily bad. This leads ...
Jack A. Orenstein
SSD
1999
Springer
97views Database» more  SSD 1999»
13 years 9 months ago
A Performance Evaluation of Spatial Join Processing Strategies
We provide an evaluation of query execution plans (QEP) in the case of queries with one or two spatial joins. The QEPs assume R -tree indexed relations and use a common set of spat...
Apostolos Papadopoulos, Philippe Rigaux, Michel Sc...