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EDBT
2008
ACM
132views Database» more  EDBT 2008»
14 years 5 months ago
Indexing high-dimensional data in dual distance spaces: a symmetrical encoding approach
Due to the well-known dimensionality curse problem, search in a high-dimensional space is considered as a "hard" problem. In this paper, a novel symmetrical encoding-bas...
Yi Zhuang, Yueting Zhuang, Qing Li, Lei Chen 0002,...
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
ICDE
2000
IEEE
168views Database» more  ICDE 2000»
14 years 6 months ago
PAC Nearest Neighbor Queries: Approximate and Controlled Search in High-Dimensional and Metric Spaces
In high-dimensional and complex metric spaces, determining the nearest neighbor (NN) of a query object ? can be a very expensive task, because of the poor partitioning operated by...
Paolo Ciaccia, Marco Patella
CIKM
2003
Springer
13 years 10 months ago
Dimensionality reduction using magnitude and shape approximations
High dimensional data sets are encountered in many modern database applications. The usual approach is to construct a summary of the data set through a lossy compression technique...
Ümit Y. Ogras, Hakan Ferhatosmanoglu
ICIP
2007
IEEE
13 years 11 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