文章基本信息

标题：Stochastic swarm clusterization method in natural language data processing
本地全文：下载
作者：Yuryev G.A. ; Verkhovskaya E.K. ; Yuryeva N.E. 等
期刊名称：Experimental Psychology (Russia)
印刷版ISSN：2072-7593
电子版ISSN：2311-7036
出版年度：2018
卷号：11
期号：3
页码：5-18
DOI：10.17759/exppsy.2018110301
出版社：Moscow State University of Psychology and Education
摘要：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.
关键词：сombinatorial optimization; particle swarm optimization; non-linear dimensionality reduction