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» Improving HLRTA*( k )
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IPL
1998
119views more  IPL 1998»
13 years 9 months ago
A 2.5-Factor Approximation Algorithm for the k-MST Problem
The k-MST problem requires finding that subset of at least k vertices of a given graph whose Minimum Spanning Tree has least weight amongst all subsets of at least k vertices. Th...
Sunil Arya, H. Ramesh
JODS
2006
135views Data Mining» more  JODS 2006»
13 years 9 months ago
Managing Uncertainty in Schema Matching with Top-K Schema Mappings
In this paper, we propose to extend current practice in schema matching with the simultaneous use of top-K schema mappings rather than a single best mapping. This is a natural ext...
Avigdor Gal
NIPS
2003
13 years 11 months ago
Learning the k in k-means
When clustering a dataset, the right number k of clusters to use is often not obvious, and choosing k automatically is a hard algorithmic problem. In this paper we present an impr...
Greg Hamerly, Charles Elkan
JCSS
2002
199views more  JCSS 2002»
13 years 9 months ago
A Constant-Factor Approximation Algorithm for the k-Median Problem
We present the first constant-factor approximation algorithm for the metric k-median problem. The k-median problem is one of the most well-studied clustering problems, i.e., those...
Moses Charikar, Sudipto Guha, Éva Tardos, D...
VLDB
2009
ACM
381views Database» more  VLDB 2009»
14 years 9 months ago
Lazy Updates: An Efficient Technique to Continuously Monitoring Reverse kNN
In this paper, we study the problem of continuous monitoring of reverse k nearest neighbor queries. Existing continuous reverse nearest neighbor monitoring techniques are sensitive...
Muhammad Aamir Cheema, Xuemin Lin, Ying Zhang, Wei...