Vezir Graflarının Girvan Newman Kümeleme Algoritması ile Modülerliği

Kümeleme veri bilimcileri tarafından teknolojik uygulamalar için yaygın olarak kullanılan veri analiz tekniğidir. Yapılan analizlerin bir kısmı veriler arasındaki ilişkiyi tanımlamaktadır ve güçlü ilişkiler, kümeleme algoritmaları aracılığıyla alt kümeler oluşturur. Kümelerin düğümleri arasındaki işlevsel ilişkiler, araştırılmamış ağ özelliklerini ortaya çıkarmaktadır. Bu çalışmada, Girvan-Newman Kümeleme algoritması ile Vezir graflarının (N-Vezir problemi graf gösterimi) ilişkisel özelliklerini araştırdık. Araştırmamız yüksek simetrik düğümlerin alt topluluklarda simetriye yol açmadığını gösterdi. Tahta büyüklüğüne göre farklı düğüm dereceleri artarken, oluşan alt kümelerin sayısı da düzensiz olarak artmaktadır. Ayrıca, maksimum modülerlik puanı alt topluluk sayısından daha yavaş artış göstermektedir.

The Modularity of Queen Graphs by Girvan-Newman Clustering Algorithm

The clustering of a given data set is a technique widely utilized data analysis method by data scientists for technological applications. Some portion of the analysis define the relations between data, and strong relations are identified as sub-communities by means of clustering algorithms. The collected functional relations between the clusters’ nodes extract the uninvestigated network properties. In this study, we investigated the relational properties of Queen graphs (graph representation of N-Queens problem) by the Girvan-Newman Clustering algorithm. Our investigation showed that the highly symmetric degree of nodes does not lead the symmetry in the sub-communities. While the distinct number of degrees increases with respect to board size, the number of subcommunities increases irregularly. Additionally, the maximum modularity score increases slower than the number of subcommunities.

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