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Unit Disk Graph-Based Node Similarity Index for Complex Network Analysis
Author
Source
Issue
Vol. 2019, Issue 2019 (31 Dec. 2019), pp.1-22, 22 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2019-03-14
Country of Publication
Egypt
No. of Pages
22
Main Subjects
Abstract EN
We seek to quantify the extent of similarity among nodes in a complex network with respect to two or more node-level metrics (like centrality metrics).
In this pursuit, we propose the following unit disk graph-based approach: we first normalize the values for the node-level metrics (using the sum of the squares approach) and construct a unit disk graph of the network in a coordinate system based on the normalized values of the node-level metrics.
There exists an edge between two vertices in the unit disk graph if the Euclidean distance between the two vertices in the normalized coordinate system is within a threshold value (ranging from 0 to k , where k is the number of node-level metrics considered).
We run a binary search algorithm to determine the minimum value for the threshold distance that would yield a connected unit disk graph of the vertices.
We refer to “1 − (minimum threshold distance / k )” as the node similarity index (NSI; ranging from 0 to 1) for the complex network with respect to the k node-level metrics considered.
We evaluate the NSI values for a suite of 60 real-world networks with respect to both neighborhood-based centrality metrics (degree centrality and eigenvector centrality) and shortest path-based centrality metrics (betweenness centrality and closeness centrality).
American Psychological Association (APA)
Meghanathan, Natarajan. 2019. Unit Disk Graph-Based Node Similarity Index for Complex Network Analysis. Complexity،Vol. 2019, no. 2019, pp.1-22.
https://search.emarefa.net/detail/BIM-1132559
Modern Language Association (MLA)
Meghanathan, Natarajan. Unit Disk Graph-Based Node Similarity Index for Complex Network Analysis. Complexity No. 2019 (2019), pp.1-22.
https://search.emarefa.net/detail/BIM-1132559
American Medical Association (AMA)
Meghanathan, Natarajan. Unit Disk Graph-Based Node Similarity Index for Complex Network Analysis. Complexity. 2019. Vol. 2019, no. 2019, pp.1-22.
https://search.emarefa.net/detail/BIM-1132559
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1132559