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COMGEO
2004
ACM
14 years 9 months ago
A local search approximation algorithm for k-means clustering
In k-means clustering we are given a set of n data points in d-dimensional space d and an integer k, and the problem is to determine a set of k points in d , called centers, to mi...
Tapas Kanungo, David M. Mount, Nathan S. Netanyahu...
CORR
1999
Springer
222views Education» more  CORR 1999»
14 years 9 months ago
Analysis of approximate nearest neighbor searching with clustered point sets
Abstract. Nearest neighbor searching is a fundamental computational problem. A set of n data points is given in real d-dimensional space, and the problem is to preprocess these poi...
Songrit Maneewongvatana, David M. Mount
ICDE
2007
IEEE
176views Database» more  ICDE 2007»
15 years 4 months ago
Finding Important People in Large News Video Databases Using Multimodal and Clustering Analysis
The wide availability of large scale databases requires more efficient and scalable tools for data understanding and knowledge discovery. In this paper, we present a method to ...
Duy-Dinh Le, Shin'ichi Satoh, Michael E. Houle, Da...
CICLING
2005
Springer
15 years 3 months ago
Name Discrimination by Clustering Similar Contexts
It is relatively common for different people or organizations to share the same name. Given the increasing amount of information available online, this results in the ever growing...
Ted Pedersen, Amruta Purandare, Anagha Kulkarni
BIOINFORMATICS
2007
195views more  BIOINFORMATICS 2007»
14 years 10 months ago
Context-dependent clustering for dynamic cellular state modeling of microarray gene expression
Motivation: High-throughput expression profiling allows researchers to study gene activities globally. Genes with similar expression profiles are likely to encode proteins that ma...
Shinsheng Yuan, Ker-Chau Li