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EUROPAR
1999
Springer
15 years 7 months ago
Parallel k/h-Means Clustering for Large Data Sets
This paper describes the realization of a parallel version of the k/h-means clustering algorithm. This is one of the basic algorithms used in a wide range of data mining tasks. We ...
Kilian Stoffel, Abdelkader Belkoniene
GECCO
2008
Springer
250views Optimization» more  GECCO 2008»
15 years 4 months ago
Community detection in social networks with genetic algorithms
A new genetic algorithm to detect communities in social networks is presented. The algorithm uses a fitness function able to identify groups of nodes in the network having dense ...
Clara Pizzuti
ERCIMDL
2000
Springer
147views Education» more  ERCIMDL 2000»
15 years 7 months ago
Map Segmentation by Colour Cube Genetic K-Mean Clustering
Segmentation of a colour image composed of different kinds of texture regions can be a hard problem, namely to compute for an exact texture fields and a decision of the optimum num...
Vitorino Ramos, Fernando Muge
EUROPAR
2003
Springer
15 years 8 months ago
A Parallel Algorithm for Incremental Compact Clustering
In this paper we propose a new parallel clustering algorithm based on the incremental construction of the compact sets of a collection of objects. This parallel algorithm is portab...
Reynaldo Gil-García, José Manuel Bad...
BMCBI
2008
204views more  BMCBI 2008»
15 years 3 months ago
EST2uni: an open, parallel tool for automated EST analysis and database creation, with a data mining web interface and microarra
Background: Expressed sequence tag (EST) collections are composed of a high number of single-pass, redundant, partial sequences, which need to be processed, clustered, and annotat...
Javier Forment, Francisco Gilabert Villamón...