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SIGGRAPH '87 Proceedings of the 14th annual conference on Computer graphics and interactive techniques
Algorithms for clustering data
Algorithms for clustering data
Term-weighting approaches in automatic text retrieval
Information Processing and Management: an International Journal
The dynamics of collective sorting robot-like ants and ant-like robots
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Representation and learning in information retrieval
Representation and learning in information retrieval
Swarm intelligence: from natural to artificial systems
Swarm intelligence: from natural to artificial systems
A clustering strategy based on a formalism of the reproductive process in natural systems
SIGIR '79 Proceedings of the 2nd annual international ACM SIGIR conference on Information storage and retrieval: information implications into the eighties
Genetic Algorithms in Search, Optimization and Machine Learning
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Parameter Selection in Particle Swarm Optimization
EP '98 Proceedings of the 7th International Conference on Evolutionary Programming VII
A new representation and operators for genetic algorithms applied to grouping problems
Evolutionary Computation
Advances in Metaheuristics for Hard Optimization (Natural Computing Series)
Advances in Metaheuristics for Hard Optimization (Natural Computing Series)
International Journal of Information Retrieval Research
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In this paper, the authors study the parameter sensitivity of the technique of particles warm optimization PSO for the clustering of data, in particular the text. They experienced the PSO parameters by varying within a range of research and we noted the best result of clustering based on three measures of assessment, internal, which is the index of Davies and Bouldin and two external based on recall and precision that are the F-measure and entropy. Every time they finished an experimentation of a parameter, it is fixed to its optimal value for the next experiment parameters. The results showed a high sensitivity of some parameters on the result of clustering.