Back close

Microscopic Structural Analysis of Complex Networks: An Empirical Study Using Motifs

Publication Type : Journal Article

Publisher : IEEE Access

Source : IEEE Access , vol. 10, pp. 33220-33229, 2022

Url : https://ieeexplore.ieee.org/abstract/document/9737093

Campus : Amritapuri

School : School of Computing

Center : AI (Artificial Intelligence) and Distributed Systems, Algorithms and Computing Systems

Year : 2022

Abstract : Complex Networks can depict a clear image of real-world systems. A real-world scenario can be represented a graph with interconnected layers - called a multilayer network. Finding motifs can give an idea of the topology of complex systems and help understand the graphs’ dynamics. Looking at motifs as atoms of the network is helpful to analyze the relationship between nodes and between layers. This work suggests a sub-graph enumeration approach to find and count the motifs in a multilayer network. The proposed work has many applications in graph mining, particularly to the structure and dynamics of complex networks.

Cite this Research Publication : Lekshmi S. Nair, Jo Cheriyan and J. Swaminathan, "Microscopic Structural Analysis of Complex Networks: An Empirical Study Using Motifs," in IEEE Access, vol. 10, pp. 33220-33229, 2022, doi: 10.1109/ACCESS.2022.3160206.

Admissions Apply Now