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» CURE: An Efficient Clustering Algorithm for Large Databases
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144
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TKDE
2002
168views more  TKDE 2002»
15 years 3 months ago
CLARANS: A Method for Clustering Objects for Spatial Data Mining
Spatial data mining is the discovery of interesting relationships and characteristics that may exist implicitly in spatial databases. To this end, this paper has three main contrib...
Raymond T. Ng, Jiawei Han
144
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BMCBI
2004
150views more  BMCBI 2004»
15 years 3 months ago
SS-Wrapper: a package of wrapper applications for similarity searches on Linux clusters
Background: Large-scale sequence comparison is a powerful tool for biological inference in modern molecular biology. Comparing new sequences to those in annotated databases is a u...
Chunlin Wang, Elliot J. Lefkowitz
135
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KDD
2001
ACM
216views Data Mining» more  KDD 2001»
16 years 4 months ago
The distributed boosting algorithm
In this paper, we propose a general framework for distributed boosting intended for efficient integrating specialized classifiers learned over very large and distributed homogeneo...
Aleksandar Lazarevic, Zoran Obradovic
ICDE
2010
IEEE
262views Database» more  ICDE 2010»
16 years 3 months ago
Approximate String Search in Spatial Databases
Abstract-- This work presents a novel index structure, MHRtree, for efficiently answering approximate string match queries in large spatial databases. The MHR-tree is based on the ...
Bin Yao, Feifei Li, Marios Hadjieleftheriou, Kun H...
DATESO
2010
233views Database» more  DATESO 2010»
15 years 1 months ago
Efficient Implementation of XPath Processor on Multi-Core CPUs
Abstract. Current XPath processors use direct approach to query evaluation which is quite inefficient in some cases and usually implemented serially. This may be a problem in case ...
Martin Krulis, Jakub Yaghob