2024
DOI: 10.1109/access.2024.3351709
|View full text |Cite
|
Sign up to set email alerts
|

Community Detection in Multiplex Networks Based on Orthogonal Nonnegative Matrix Tri-Factorization

Meiby Ortiz-Bouza,
Selin Aviyente

Abstract: Networks are commonly used to model complex systems. The different entities in the system are represented by nodes of the network and their interactions by edges. In most real life systems, the different entities may interact in different ways necessitating the use of multiplex networks where multiple links are used to model the interactions. One of the major tools for inferring network topology is community detection. Although there are numerous works on community detection in single-layer networks, existing … Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
2

Citation Types

0
4
0

Year Published

2024
2024
2024
2024

Publication Types

Select...
5
1

Relationship

0
6

Authors

Journals

citations
Cited by 7 publications
(4 citation statements)
references
References 67 publications
0
4
0
Order By: Relevance
“…Ref. [30] proposed an orthogonal non-negative matrix tri-factorization approach for community discovery in multiplex networks. The algorithm decomposes the adjacency matrix A of each layer into two terms, each of which is an orthogonal non-negative matrix tri-factorization.…”
Section: Community Detection With Nmf In Multiplex Networkmentioning
confidence: 99%
See 3 more Smart Citations
“…Ref. [30] proposed an orthogonal non-negative matrix tri-factorization approach for community discovery in multiplex networks. The algorithm decomposes the adjacency matrix A of each layer into two terms, each of which is an orthogonal non-negative matrix tri-factorization.…”
Section: Community Detection With Nmf In Multiplex Networkmentioning
confidence: 99%
“…This will lead to the model becoming more and more complex. For a multiplex network, the model in [30] only divides the community in a multiplex network into common communities and private communities. However, it does not perform a separate study of the separate common and private communities.…”
Section: Community Detection With Nmf In Multiplex Networkmentioning
confidence: 99%
See 2 more Smart Citations