Geodesic
A hybrid clustering algorithm based on PSO with dynamic crossover
Nečetkie sistemy i mâgkie vyčisleniâ, Tome 12 (2017) no. 2, pp. 87-96

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In this paper an approach to clustering of short text fragments by hierarchical classifier is proposed. This approach is based on a special way of object representation in the dimension of features constructed by hierarchical classifier. Also, in order to reasonable perform quality evaluation of clustering results there is a set of criteria proposed in this paper. Presented experimental results show the ability of this approach to improve significantly the quality of clustering.
Keywords: clustering, fuzzy classifier, natural language processing, evaluation of clustering. 
@article{FSSC_2017_12_2_a0,
     author = {P. V. Dudarin and N. G. Yarushkina},
     title = {A hybrid clustering algorithm based on {PSO} with dynamic crossover},
     journal = {Ne\v{c}etkie sistemy i m\^agkie vy\v{c}isleni\^a},
     pages = {87--96},
     publisher = {mathdoc},
     volume = {12},
     number = {2},
     year = {2017},
     language = {ru},
     url = {http://geodesic.mathdoc.fr/item/FSSC_2017_12_2_a0/}
}
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P. V. Dudarin; N. G. Yarushkina. A hybrid clustering algorithm based on PSO with dynamic crossover. Nečetkie sistemy i mâgkie vyčisleniâ, Tome 12 (2017) no. 2, pp. 87-96. http://geodesic.mathdoc.fr/item/FSSC_2017_12_2_a0/