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Experimental Psychology (Russia)
2018. Vol. 11, no. 3, 5–18
doi:10.17759/exppsy.2018110301
ISSN: 2072-7593 / 2311-7036 (online)

Stochastic swarm clusterization method in natural language data processing

419

G.A. Yuryev, E.K. Verkhovskaya, N.E. Yuryeva

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Abstract

Consider natural language data processing technology based on non-linear dimensionality reduction method which takes into account the discriminating power of the solution found for given values of the categorical variable associated with each observation. Stochastic optimization method known as the “Particle swarm optimization” is proposed to found characteristics that ensure the best separation of observations in terms of a given quality functional. The basis for evaluating the quality of the solution lies in the purity of the clusters obtained with the k-means method, or with using self-organizing Kohonen feature maps.

General Information

Keywords: сombinatorial optimization, particle swarm optimization, non-linear dimensionality reduction

Journal rubric: Mathematical Psychology

Article type: scientific article

DOI: https://doi.org/10.17759/exppsy.2018110301

For citation: Yuryev G.A., Verkhovskaya E.K., Yuryeva N.E. Stochastic swarm clusterization method in natural language data processing. Eksperimental'naâ psihologiâ = Experimental Psychology (Russia), 2018. Vol. 11, no. 3, pp. 5–18. DOI: 10.17759/exppsy.2018110301. (In Russ., аbstr. in Engl.)

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Information About the Authors

Grigory A. Yuryev, PhD in Physics and Matematics, Associate Professor, Head of Department of the Computer Science Faculty, Leading Researcher, Youth Laboratory Information Technologies for Psychological Diagnostics, Moscow State University of Psychology and Education, Moscow, Russia, ORCID: https://orcid.org/0000-0002-2960-6562, e-mail: g.a.yuryev@gmail.com

E. K. Verkhovskaya, Researcher, Moscow State University of Psychology and Education, Moscow, Russia, e-mail: katrin636bmw@yandex.ru

Nataliya E. Yuryeva, PhD in Engineering, Head of Laboratory, Youth Laboratory Information Technologies for Psychological Diagnostics, Research Fellow, Information Technology Center for Psychological Studies of the Computer Science Faculty, Moscow State University of Psychology and Education, Moscow, Russia, ORCID: https://orcid.org/0000-0003-1419-876X, e-mail: yurieva.ne@gmail.com

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