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TKDE
2011
332views more  TKDE 2011»
12 years 9 months ago
Adaptive Cluster Distance Bounding for High-Dimensional Indexing
—We consider approaches for similarity search in correlated, high-dimensional data-sets, which are derived within a clustering framework. We note that indexing by “vector appro...
Sharadh Ramaswamy, Kenneth Rose
ICIP
2007
IEEE
13 years 8 months ago
Adaptive Cluster-Distance Bounding for Nearest Neighbor Search in Image Databases
We consider approaches for exact similarity search in a high dimensional space of correlated features representing image datasets, based on principles of clustering and vector qua...
Sharadh Ramaswamy, Kenneth Rose
ADC
2003
Springer
123views Database» more  ADC 2003»
13 years 7 months ago
A Distance-Based Packing Method for High Dimensional Data
Minkowski-sum cost model indicates that balanced data partitioning is not beneficial for high dimensional data. Thus we study several unbalanced partitioning methods and propose ...
Tae-wan Kim, Ki-Joune Li
ICDE
2003
IEEE
193views Database» more  ICDE 2003»
14 years 3 months ago
An Adaptive and Efficient Dimensionality Reduction Algorithm for High-Dimensional Indexing
The notorious "dimensionality curse" is a well-known phenomenon for any multi-dimensional indexes attempting to scale up to high dimensions. One well known approach to o...
Hui Jin, Beng Chin Ooi, Heng Tao Shen, Cui Yu, Aoy...
VLDB
2000
ACM
229views Database» more  VLDB 2000»
13 years 6 months ago
Local Dimensionality Reduction: A New Approach to Indexing High Dimensional Spaces
Many emerging application domains require database systems to support efficient access over highly multidimensional datasets. The current state-of-the-art technique to indexing hi...
Kaushik Chakrabarti, Sharad Mehrotra