Back to Search
Start Over
A Graph-Cut-Based Approach to Community Detection in Networks.
- Source :
- Applied Sciences (2076-3417); Jun2022, Vol. 12 Issue 12, p6218, 17p
- Publication Year :
- 2022
-
Abstract
- Networks can be used to model various aspects of our lives as well as relations among many real-world entities and objects. To detect a community structure in a network can enhance our understanding of the characteristics, properties, and inner workings of the network. Therefore, there has been significant research on detecting and evaluating community structures in networks. Many fields, including social sciences, biology, engineering, computer science, and applied mathematics, have developed various methods for analyzing and detecting community structures in networks. In this paper, a new community detection algorithm, which repeats the process of dividing a community into two smaller communities by finding a minimum cut, is proposed. The proposed algorithm is applied to some example network data and shows fairly good community detection results with comparable modularity Q values. [ABSTRACT FROM AUTHOR]
- Subjects :
- APPLIED mathematics
COMPUTER science
ALGORITHMS
Subjects
Details
- Language :
- English
- ISSN :
- 20763417
- Volume :
- 12
- Issue :
- 12
- Database :
- Complementary Index
- Journal :
- Applied Sciences (2076-3417)
- Publication Type :
- Academic Journal
- Accession number :
- 157640023
- Full Text :
- https://doi.org/10.3390/app12126218