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» On Approximating the Radii of Point Sets in High Dimensions
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PCM
2001
Springer
183views Multimedia» more  PCM 2001»
14 years 2 days 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
CIKM
2003
Springer
14 years 26 days ago
High dimensional reverse nearest neighbor queries
Reverse Nearest Neighbor (RNN) queries are of particular interest in a wide range of applications such as decision support systems, profile based marketing, data streaming, docum...
Amit Singh, Hakan Ferhatosmanoglu, Ali Saman Tosun
SODA
2003
ACM
126views Algorithms» more  SODA 2003»
13 years 9 months ago
Smaller core-sets for balls
We prove the existence of small core-sets for solving approximate k-center clustering and related problems. The size of these core-sets is considerably smaller than the previously...
Mihai Badoiu, Kenneth L. Clarkson
VLDB
2000
ACM
166views Database» more  VLDB 2000»
13 years 11 months ago
What Is the Nearest Neighbor in High Dimensional Spaces?
Nearest neighbor search in high dimensional spaces is an interesting and important problem which is relevant for a wide variety of novel database applications. As recent results s...
Alexander Hinneburg, Charu C. Aggarwal, Daniel A. ...
PODS
1997
ACM
182views Database» more  PODS 1997»
13 years 11 months ago
A Cost Model For Nearest Neighbor Search in High-Dimensional Data Space
In this paper, we present a new cost model for nearest neighbor search in high-dimensional data space. We first analyze different nearest neighbor algorithms, present a generaliza...
Stefan Berchtold, Christian Böhm, Daniel A. K...