Clustering of Data Represented by Pairwise Comparisons

Sergey Dvoenko

doi:10.2478/candc-2022-0021

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Clustering of Data Represented by Pairwise Comparisons

Control and Cybernetics

Volume 51 (2022): Issue 3 (September 2022)

By: Sergey Dvoenko

Open Access

|Mar 2023

Abstract

In this paper, experimental data, given in the form of pairwise comparisons, such as distances or similarities, are considered. Clustering algorithms for processing such data are developed based on the well-known k-means procedure. Relations to factor analysis are shown. The problems of improving clustering quality and of finding the proper number of clusters in the case of pairwise comparisons are considered. Illustrative examples are provided.

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Articles in this issue

DOI: https://doi.org/10.2478/candc-2022-0021 | Journal eISSN: 2720-4278 | Journal ISSN: 0324-8569

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Language: English

Page range: 343 - 387

Submitted on: Aug 1, 2022

Accepted on: Sep 1, 2022

Published on: Mar 22, 2023

Published by: Systems Research Institute Polish Academy of Sciences

In partnership with: Paradigm Publishing Services

Publication frequency: 4 issues per year

Keywords:

-means,

Related subjects:

Computer sciences, other,

Engineering,

Electrical engineering,

Fundamentals of electrical engineering,

Mechanical engineering,

Fundamentals of mechanical engineering,

Mathematics,

General mathematics

© 2023 Sergey Dvoenko, published by Systems Research Institute Polish Academy of Sciences
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Volume 51 (2022): Issue 3 (September 2022)