Analysis of Graph-based Cluster Core Separation using a new Core Separability Index

Адилова, Ф.Т., Давронов, Р.Р.

Рақамли технологияларнинг назарий ва амалий масалалари · 2025-yil

Annotatsiya

This article presents a new internal validity index of clustering called the Core Separation Index (CSI), designed to improve the quality and automate graph-based density clustering algorithms. The proposed index assesses the quality of cluster nucleus separation by measuring the ratio between the internal cohesion of each nucleus and its coupling with other nuclei. We present the theoretical basis of the CSI index, the theorem about its properties, and a strict proof. The index is integrated into the algorithm based on graph density variation analysis (GDVA), which allows for the automatic determination of optimal clustering parameters. A comprehensive experimental comparison of the CSI index with existing indices, such as DVI (density-based cluster validity indices), Silhouette, and Dunn, was carried out on five sets of synthetic data of different structures. The results, assessed using the external metrics Adjusted Rand Index (ARI) and Normalized Mutual Information (NMI), show that CSI provides the best clustering quality (average NMI 0.7460), significantly exceeding other indices in calculation speed (average 0.17s). A high correlation of the proposed index with external quality indicators is also shown, which confirms its reliability for assessing and selecting the optimal structure of clusters.

Maqola ma’lumotlari
MualliflarАдилова, Ф.Т., Давронов, Р.Р.
JurnalРақамли технологияларнинг назарий ва амалий масалалари
NashriyotТАТУ Самарқанд филиали
ISSN2181-3086, 2181-3094
Nashr sanasi2025-11-27
Jild8
Son4
Betlar129-137
TilIngliz
Ilmiy sohaTexnika
DOI10.62132/ijdt.v8i4.313
Indeksga qo‘shilgan2026-08-26

DOI: 10.62132/ijdt.v8i4.313 · Maqolaning asl sahifasi

Kalit so‘zlar

кластерный анализ, кластеризация на основе графов, плотностная кластеризация, индекс валидности кластеров, GDVA, CSI, автоматическое определение параметров, ARI, NMI, cluster analysis, graph-based clustering, density clustering, cluster validity index, GDVA, CSI, automatic parameter determination, ARI, NMI

Ilmiy soha

Texnika

Iqtibos keltirish

APAАдилова, Ф.Т., & Давронов, Р.Р. (2025). Analysis of Graph-based Cluster Core Separation using a new Core Separability Index. Рақамли технологияларнинг назарий ва амалий масалалари, 8(4), 129-137. https://doi.org/10.62132/ijdt.v8i4.313
GOST (OAK)Адилова, Ф.Т., Давронов, Р.Р. Analysis of Graph-based Cluster Core Separation using a new Core Separability Index // Рақамли технологияларнинг назарий ва амалий масалалари. – 2025. – T. 8, № 4. – P. 129-137. – DOI: 10.62132/ijdt.v8i4.313.
MLAАдилова, Ф.Т., and Давронов, Р.Р. “Analysis of Graph-based Cluster Core Separation using a new Core Separability Index.” Рақамли технологияларнинг назарий ва амалий масалалари, 8(4), 129-137, 2025. https://doi.org/10.62132/ijdt.v8i4.313
ChicagoАдилова, Ф.Т., and Давронов, Р.Р. “Analysis of Graph-based Cluster Core Separation using a new Core Separability Index.” Рақамли технологияларнинг назарий ва амалий масалалари, 8(4), 129-137 (2025). https://doi.org/10.62132/ijdt.v8i4.313
HarvardАдилова, Ф.Т., and Давронов, Р.Р (2025) ‘Analysis of Graph-based Cluster Core Separation using a new Core Separability Index’, Рақамли технологияларнинг назарий ва амалий масалалари, 8(4), 129-137. https://doi.org/10.62132/ijdt.v8i4.313
BibTeX
@article{article2025,
  title = {Analysis of Graph-based Cluster Core Separation using a new Core Separability Index},
  author = {Адилова, Ф.Т. and Давронов, Р.Р.},
  journal = {Рақамли технологияларнинг назарий ва амалий масалалари},
  year = {2025},
  volume = {8},
  number = {4},
  pages = {129-137},
  doi = {10.62132/ijdt.v8i4.313},
  url = {https://doi.org/10.62132/ijdt.v8i4.313}
}

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