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EUROPAR
1999
Springer
14 years 14 hour 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»
13 years 8 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»
13 years 11 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
14 years 29 days 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»
13 years 7 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...