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Creators/Authors contains: "Tillquist, Richard"

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  1. The metric dimension of a graph is the smallest number of nodes required to identify allother nodes uniquely based on shortest path distances. Applications of metric dimensioninclude discovering the source of a spread in a network, canonically labeling graphs, andembedding symbolic data in low-dimensional Euclidean spaces. This survey gives a self-contained introduction to metric dimension and an overview of the quintessential resultsand applications. We discuss methods for approximating the metric dimension of generalgraphs, and specific bounds and asymptotic behavior for deterministic and random familiesof graphs. We conclude with related concepts and directions for future work. 
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