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DASFAA
2005
IEEE
120views Database» more  DASFAA 2005»
13 years 10 months ago
A New Indexing Method for High Dimensional Dataset
Indexing high dimensional datasets has attracted extensive attention from many researchers in the last decade. Since R-tree type of index structures are known as suffering “curse...
Jiyuan An, Yi-Ping Phoebe Chen, Qinying Xu, Xiaofa...
ISM
2006
IEEE
174views Multimedia» more  ISM 2006»
13 years 11 months ago
Fast Similarity Search for High-Dimensional Dataset
This paper addresses the challenging problem of rapidly searching and matching high-dimensional features for the applications of multimedia database retrieval and pattern recognit...
Quan Wang, Suya You
VLDB
2000
ACM
229views Database» more  VLDB 2000»
13 years 8 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
TKDE
2011
332views more  TKDE 2011»
12 years 12 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
ICDE
2003
IEEE
193views Database» more  ICDE 2003»
14 years 6 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...