42 citations · 169 across the 26 of their papers we have counts for
26 papers
Exploratory Factory Analysis of the Centrality Metrics for Complex Real-World Networks
Natarajan Meghanathan
Exploratory factor analysis (EFA) is useful to identify the number and mapping of the hidden factors that could dominantly represent the features in the dataset. Principal componen…
Node Dissimilarity Index for Complex Network Analysis
Natarajan Meghanathan
We propose a principal component analysis (PCA)-based approach to quantify (the node dissimilarity index, NDI) the extent of dissimilarity among nodes in a network with respect to…
Core-Intermediate-Peripheral Index: Factor Analysis of Neighborhood and Shortest Paths-based Centrality Metrics
Natarajan Meghanathan
We perform factor analysis on the raw data of the four major neighborhood and shortest paths-based centrality metrics (Degree, Eigenvector, Betweeenness and Closeness) and propose…
Neighborhood-based Bridge Node Centrality Tuple for Preferential Vaccination of Nodes
Natarajan Meghanathan
We investigate the use of a recently proposed centrality tuple called the Neighborhood-based Bridge Node Centrality (NBNC) tuple to choose nodes for preferential vaccination so tha…
Use of Eigenvector Centrality to Detect Graph Isomorphism
Natarajan Meghanathan
Graph Isomorphism is one of the classical problems of graph theory for which no deterministic polynomial-time algorithm is currently known, but has been neither proven to be NP-com…
Probabilistic Diffusion in Random Network Graphs
Natarajan Meghanathan
In this paper, we consider a random network such that there could be a link between any two nodes in the network with a certain probability (plink). Diffusion is the phenomenon of…