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ALGORITHM OF HIERARCHICAL MATRIX CLUSTERIZATION AND ITS APPLICATIONS. / Лежнина, Елена Александровна; Калинина, Елизавета Александровна.

в: Contributions to Game Theory and Management, Том 15, 12.2022, стр. 178-188.

Результаты исследований: Научные публикации в периодических изданияхстатьяРецензирование

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@article{fac5bce23f594be59e65098f0454125c,
title = "ALGORITHM OF HIERARCHICAL MATRIX CLUSTERIZATION AND ITS APPLICATIONS",
abstract = "In this article, the problem of hierarchial matrix clusterization is discussed. For this, the influence of individuals on the community was used. The problem of dividing the community into groups of related participants has been solved, an appropriate algorithm for finding the most influential community agents has been proposed. Clustering was carried out using an algorithm for reducing the adjacency matrix of a directed graph with nodes representing members of a social network and edges representing relationships between them. The applications to the problems of working groups, advertising in social networks and complex technical systems are considered.",
author = "Лежнина, {Елена Александровна} and Калинина, {Елизавета Александровна}",
year = "2022",
month = dec,
language = "русский",
volume = "15",
pages = "178--188",
journal = "Contributions to Game Theory and Management",
issn = "2310-2608",

}

RIS

TY - JOUR

T1 - ALGORITHM OF HIERARCHICAL MATRIX CLUSTERIZATION AND ITS APPLICATIONS

AU - Лежнина, Елена Александровна

AU - Калинина, Елизавета Александровна

PY - 2022/12

Y1 - 2022/12

N2 - In this article, the problem of hierarchial matrix clusterization is discussed. For this, the influence of individuals on the community was used. The problem of dividing the community into groups of related participants has been solved, an appropriate algorithm for finding the most influential community agents has been proposed. Clustering was carried out using an algorithm for reducing the adjacency matrix of a directed graph with nodes representing members of a social network and edges representing relationships between them. The applications to the problems of working groups, advertising in social networks and complex technical systems are considered.

AB - In this article, the problem of hierarchial matrix clusterization is discussed. For this, the influence of individuals on the community was used. The problem of dividing the community into groups of related participants has been solved, an appropriate algorithm for finding the most influential community agents has been proposed. Clustering was carried out using an algorithm for reducing the adjacency matrix of a directed graph with nodes representing members of a social network and edges representing relationships between them. The applications to the problems of working groups, advertising in social networks and complex technical systems are considered.

M3 - статья

VL - 15

SP - 178

EP - 188

JO - Contributions to Game Theory and Management

JF - Contributions to Game Theory and Management

SN - 2310-2608

ER -

ID: 102655702