On Clustering Detection Based on a Quadratic Program in Hypergraphs

A proper cluster is usually defined as maximally coherent groups from a set of objects using pairwise or more complicated similarities. In general hypergraphs, clustering problem refers to extraction of subhypergraphs with a higher internal density, for instance, maximal cliques in hypergraphs. The...

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Main Author: Qingsong Tang
Format: Article
Language:English
Published: Wiley 2022-01-01
Series:Journal of Mathematics
Online Access:http://dx.doi.org/10.1155/2022/4840964
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author Qingsong Tang
author_facet Qingsong Tang
author_sort Qingsong Tang
collection DOAJ
description A proper cluster is usually defined as maximally coherent groups from a set of objects using pairwise or more complicated similarities. In general hypergraphs, clustering problem refers to extraction of subhypergraphs with a higher internal density, for instance, maximal cliques in hypergraphs. The determination of clustering structure within hypergraphs is a significant problem in the area of data mining. Various works of detecting clusters on graphs and uniform hypergraphs have been published in the past decades. Recently, it has been shown that the maximum 1,2-clique size in 1,2-hypergraphs is related to the global maxima of a certain quadratic program based on the structure of the given nonuniform hypergraphs. In this paper, we first extend this result to relate strict local maxima of this program to certain maximal cliques including 2-cliques or 1,2-cliques. We also explore the connection between edge-weighted clusters and strictly local optimum solutions of a class of polynomials resulting from nonuniform 1,2-hypergraphs.
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institution Kabale University
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spelling doaj-art-bc676cd26d38428fb95fe81a25832f2d2025-02-03T01:04:31ZengWileyJournal of Mathematics2314-47852022-01-01202210.1155/2022/4840964On Clustering Detection Based on a Quadratic Program in HypergraphsQingsong Tang0College of SciencesA proper cluster is usually defined as maximally coherent groups from a set of objects using pairwise or more complicated similarities. In general hypergraphs, clustering problem refers to extraction of subhypergraphs with a higher internal density, for instance, maximal cliques in hypergraphs. The determination of clustering structure within hypergraphs is a significant problem in the area of data mining. Various works of detecting clusters on graphs and uniform hypergraphs have been published in the past decades. Recently, it has been shown that the maximum 1,2-clique size in 1,2-hypergraphs is related to the global maxima of a certain quadratic program based on the structure of the given nonuniform hypergraphs. In this paper, we first extend this result to relate strict local maxima of this program to certain maximal cliques including 2-cliques or 1,2-cliques. We also explore the connection between edge-weighted clusters and strictly local optimum solutions of a class of polynomials resulting from nonuniform 1,2-hypergraphs.http://dx.doi.org/10.1155/2022/4840964
spellingShingle Qingsong Tang
On Clustering Detection Based on a Quadratic Program in Hypergraphs
Journal of Mathematics
title On Clustering Detection Based on a Quadratic Program in Hypergraphs
title_full On Clustering Detection Based on a Quadratic Program in Hypergraphs
title_fullStr On Clustering Detection Based on a Quadratic Program in Hypergraphs
title_full_unstemmed On Clustering Detection Based on a Quadratic Program in Hypergraphs
title_short On Clustering Detection Based on a Quadratic Program in Hypergraphs
title_sort on clustering detection based on a quadratic program in hypergraphs
url http://dx.doi.org/10.1155/2022/4840964
work_keys_str_mv AT qingsongtang onclusteringdetectionbasedonaquadraticprograminhypergraphs