SIGKDD
2000
14 years 6 days ago
2000
This paper presents a simple new algorithm that performs k-means clustering in one scan of a dataset, while using a bu er for points from the dataset of xed size. Experiments show...
TKDE
2008
14 years 10 days ago
2008
Given a dataset P, a k-means query returns k points in space (called centers), such that the average squared distance between each point in P and its nearest center is minimized. S...
ALGORITHMICA
2005
14 years 10 days ago
2005
We present polynomial upper and lower bounds on the number of iterations performed by the k-means method (a.k.a. Lloyd's method) for k-means clustering. Our upper bounds are ...
IJBRA
2007
14 years 11 days ago
2007
: Document clustering has been used for better document retrieval and text mining. In this paper, we investigate if a biomedical ontology improves biomedical literature clustering ...
PAMI
2006
14 years 11 days ago
2006
The k-means algorithm is widely used for clustering because of its computational efficiency. Given n points in d-dimensional space and the number of desired clusters k, k-means see...
PR
2008
14 years 11 days ago
2008
Clustering in gene expression data sets is a challenging problem. Different algorithms for clustering of genes have been proposed. However due to the large number of genes only a ...
IDA
2007
Springer
14 years 11 days ago
2007
Springer
The performance of K-means and Gaussian mixture model (GMM) clustering depends on the initial guess of partitions. Typically, clus∗ corresponding author 1
KAIS
2006
14 years 12 days ago
2006
Clustering has been one of the most widely studied topics in data mining and k-means clustering has been one of the popular clustering algorithms. K-means requires several passes ...
CORR
2008
Springer
14 years 16 days ago
2008
Springer
The k-means method is a widely used clustering algorithm. One of its distinguished features is its speed in practice. Its worst-case running-time, however, is exponential, leaving...
BMCBI
2008
14 years 17 days ago
2008
Background: DNA microarrays, which determine the expression levels of tens of thousands of genes from a sample, are an important research tool. However, the volume of data they pr...