As a summary, Table 1 demonstrates the differences between all the mentioned graphs in terms of different behaviors and definitions.
Van Rooij and Wilf [ 9] gave a characterization of line graphs in terms of nine forbidden subgraphs.
In non-technical terms, the first two assumptions mean that with the exception of empirical information equivalency relations between SNPs, there is a direct correspondence between data and directed acyclic data-generative graph in terms of statistical relations.
We characterise quasidiagonality of the C⁎-algebra of a cofinal k-graph in terms of an algebraic condition involving the coordinate matrices of the graph.
Graphs offer a visualization of the relationship between negotiators in terms of distance/closeness of offers and counteroffers and movements toward or away from each other.
The use of data sets from two different mammalian species (macaque monkey and cat) invites comparisons between these structures in terms of a broad range of graph theoretical measures, including small-world attributes, motif composition and centrality.
end{aligned}It measures the difference between (mathsf {GPARs}) in terms of the Jaccard distance of their match sets, by treating (R_1) and (R_2) as graph patterns.
Modern ontologies are typically viewed as graphs in which vertices represent terms or concepts in the domain of interest, and edges represent relational ties between terms (e.g. is-a, part-of).
Further, similarity between entities in a graph can be measured recursively in terms of the similarity of their neighbors, e.g. SimRank (5).
In terms of graph topology, this could be captured by a small, linearly connected, graph structure.
