Metaheuristic for Community Detection in Graph

Student: Nikolaev Nikita

Supervisor: Irina Evgenievna Utkina

Faculty: Faculty of Informatics, Mathematics, and Computer Science (HSE Nizhny Novgorod)

Educational Programme: Applied Mathematics and Information Science (Bachelor)

Year of Graduation: 2017

In the framework of this paper, an attempt was made to implement a method whose idea is to analyze a list of parameters embedded in the graph structure (for example, the number of vertices and edges, density, etc.) and to determine the most suitable clustering algorithm for the given graph, using one of the classification algorithms. Graphs, for which the true structure of the communities was known, were used for training the classification algorithm, therefore, using certain clustering performance evaluation metrics, it was possible to determine which of the applied algorithms of finding communities shows the most accurate results. The paper dealt only with non-oriented unweighted graphs without loops and multiple edges.

Student Theses at HSE must be completed in accordance with the University Rules and regulations specified by each educational programme.

Summaries of all theses must be published and made freely available on the HSE website.

The full text of a thesis can be published in open access on the HSE website only if the authoring student (copyright holder) agrees, or, if the thesis was written by a team of students, if all the co-authors (copyright holders) agree. After a thesis is published on the HSE website, it obtains the status of an online publication.

Student theses are objects of copyright and their use is subject to limitations in accordance with the Russian Federation’s law on intellectual property.

In the event that a thesis is quoted or otherwise used, reference to the author’s name and the source of quotation is required.

Search all student theses