Metric Dimension and Resolvability of Jaccard Spaces
Manuel E. Lladser, Alexander J. Paradise

TL;DR
This paper investigates the metric dimension of Jaccard spaces formed by the power set of a finite set, providing probabilistic constructions of nearly minimal resolving sets and analyzing their size relative to the set's cardinality.
Contribution
It introduces a probabilistic method to construct nearly optimal resolving sets for Jaccard spaces and determines their size as proportional to |X|/ln|X|.
Findings
The metric dimension of (2^X, Jac) is Θ(|X|/ln|X|).
A smaller subset can resolve pairs of subsets of size up to √|X|/ln|X| with high probability.
Probabilistic and linear algebra techniques effectively construct resolving sets in Jaccard spaces.
Abstract
A subset of points in a metric space is said to resolve it if each point in the space is uniquely characterized by its distance to each point in the subset. In particular, resolving sets can be used to represent points in abstract metric spaces as Euclidean vectors. Importantly, due to the triangle inequality, points close by in the space are represented as vectors with similar coordinates, which may find applications in classification problems of symbolic objects under suitably chosen metrics. In this manuscript, we address the resolvability of Jaccard spaces, i.e., metric spaces of the form , where is the power set of a finite set , and is the Jaccard distance between subsets of . Specifically, for different , , where denotes size (i.e., cardinality) and denotes the…
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Taxonomy
TopicsDigital Image Processing Techniques · Advanced Numerical Analysis Techniques · Advanced Topology and Set Theory
MethodsSparse Evolutionary Training
