A Combined Algorithm Based on Fuzzy Clustering for Textual Information Analysis

In modern information systems the task of analyzing a large volume of textual information is essential. In this case, the issues related to the automation of the construction of semantic evaluations of the transmitted text information are of particular importance. In this paper we propose to use a c...

Full description

Saved in:
Bibliographic Details
Published in2023 5th International Conference on Control Systems, Mathematical Modeling, Automation and Energy Efficiency (SUMMA) pp. 702 - 706
Main Authors Gromov, Y.Y., Karasev, P.I., Shelpuck, M.I., Antonov, E.V., Dhahir Al-Ameedee, Mustafa Abdulkadhim
Format Conference Proceeding
LanguageEnglish
Published IEEE 08.11.2023
Subjects
Approximation algorithms
Automation
classification
clustering
Clustering algorithms
Data analysis
Graphics
Mathematical models
Semantics
Task analysis
Online AccessGet full text

Cover

More Information
Summary:In modern information systems the task of analyzing a large volume of textual information is essential. In this case, the issues related to the automation of the construction of semantic evaluations of the transmitted text information are of particular importance. In this paper we propose to use a combined algorithm that allows increasing the efficiency of semantic evaluations of large volumes of text information. Clustering is of one of the approaches to solving optimization problems that are determining the structuring (effective in terms of time costs) of large amounts of textual information.
DOI:10.1109/SUMMA60232.2023.10349402