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International Journal of Information Technology Research and Applications
Article . 2023 . Peer-reviewed
License: CC BY SA
Data sources: Crossref
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Square Distance in Graphs

Authors: null V. Thamarai Selvi; null Pandian Vaidhyanathan;

Square Distance in Graphs

Abstract

In this paper, we consider a simple connected graph having no loops and multiple edges. The order and size of are denoted by and respectively in graphs is a wide branch of graph theory having many scientific and real-life applications. There are various types of distances studied in the literature.The distance is the length of the shortest path between the vertices and in [2]. The detour distance is the length of the longest path between the vertices and in [3]. The concept of centrality widely applied in social network analysis. Degree centrality is the simplest centrality measure to compute centre. Betweenness centrality measures used for analyzed cancer network.

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    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
gold
Related to Research communities
Cancer Research