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VLDB
2000
ACM
114views Database» more  VLDB 2000»
13 years 8 months ago
The A-tree: An Index Structure for High-Dimensional Spaces Using Relative Approximation
We propose a novel index structure, A-tree (Approximation tree), for similarity search of high-dimensional data. The basic idea of the
Yasushi Sakurai, Masatoshi Yoshikawa, Shunsuke Uem...
SIGMOD
2009
ACM
235views Database» more  SIGMOD 2009»
14 years 5 months ago
Quality and efficiency in high dimensional nearest neighbor search
Nearest neighbor (NN) search in high dimensional space is an important problem in many applications. Ideally, a practical solution (i) should be implementable in a relational data...
Yufei Tao, Ke Yi, Cheng Sheng, Panos Kalnis
PCM
2001
Springer
183views Multimedia» more  PCM 2001»
13 years 9 months ago
An Adaptive Index Structure for High-Dimensional Similarity Search
A practical method for creating a high dimensional index structure that adapts to the data distribution and scales well with the database size, is presented. Typical media descrip...
Peng Wu, B. S. Manjunath, Shivkumar Chandrasekaran
ICDE
2007
IEEE
124views Database» more  ICDE 2007»
14 years 6 months ago
On MBR Approximation of Histories for Historical Queries: Expectations and Limitations
Traditional approaches for efficiently processing historical queries, where a history is a multidimensional timeseries, employ a two step filter-and-refine scheme. In the filter s...
Reza Sherkat, Davood Rafiei
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