Abstract

This paper contains a description of computational experiments on the application of elastic maps to the analysis of time-varying volumes of textual information. Elastic maps are considered as a tool to provide analytical work with textual information and large information arrays of data. This paper presents the results of numerical experiments on the study of data volumes consisting of frequencies of joint use of words from different parts of speech, for instance “noun + verb” or “adjective + noun”. We consider text collections in Russian for experiments. Previously, static information arrays were mostly considered. It is for them methods of data analysis and methods of visual analytics were developed. Nevertheless, data comes in all the time in various areas of human activity. And in practice it is necessary to know how the cluster picture of multidimensional data volume changes over time. The paper describes the numerical experiments for real time-varying multidimensional data sets. Such experiments allows to analyze the evolution of cluster structure for multidimensional data and to trace the evolution for separate cluster.

Details

Title
VISUAL ANALYSIS OF TIME-VARYING MULTIDIMENSIONAL DATA SETS
Author
Bondarev, A E 1 

 Keldysh Institute of Applied Mathematics RAS, Moscow, Russia; Keldysh Institute of Applied Mathematics RAS, Moscow, Russia 
Pages
41-45
Publication year
2023
Publication date
2023
Publisher
Copernicus GmbH
ISSN
16821750
e-ISSN
21949034
Source type
Conference Paper
Language of publication
English
ProQuest document ID
2812748653
Copyright
© 2023. This work is published under https://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.