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» CURE: An Efficient Clustering Algorithm for Large Databases
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115
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IPPS
2010
IEEE
15 years 1 months ago
Large-scale multi-dimensional document clustering on GPU clusters
Document clustering plays an important role in data mining systems. Recently, a flocking-based document clustering algorithm has been proposed to solve the problem through simulat...
Yongpeng Zhang, Frank Mueller, Xiaohui Cui, Thomas...
128
Voted
TSMC
2002
110views more  TSMC 2002»
15 years 3 months ago
Complexity reduction for "large image" processing
We present a method for sampling feature vectors in large (e.g., 2000 5000 16 bit) images that finds subsets of pixel locations which represent "regions" in the image. Sa...
Nikhil R. Pal, James C. Bezdek
124
Voted
ICDAR
2003
IEEE
15 years 9 months ago
A Low-Cost Parallel K-Means VQ Algorithm Using Cluster Computing
In this paper we propose a parallel approach for the Kmeans Vector Quantization (VQ) algorithm used in a twostage Hidden Markov Model (HMM)-based system for recognizing handwritte...
Alceu de Souza Britto Jr., Paulo Sergio Lopes de S...
156
Voted
PAMI
2006
134views more  PAMI 2006»
15 years 3 months ago
A Genetic Algorithm Using Hyper-Quadtrees for Low-Dimensional K-means Clustering
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...
Michael Laszlo, Sumitra Mukherjee
248
Voted
ICDE
2009
IEEE
156views Database» more  ICDE 2009»
16 years 5 months ago
Distributed Structural Relaxation of XPath Queries
Due to the structural heterogeneity of XML, queries are often interpreted approximately. This is achieved by relaxing the query and ranking the results based on their relevance to ...
Georgia Koloniari, Evaggelia Pitoura