Enregistré dans:
Détails bibliographiques
Auteurs principaux: Boldi, Paolo, Furia, Flavio, Prezioso, Chiara, Stewart, Ian
Format: Preprint
Publié: 2025
Sujets:
Accès en ligne:https://arxiv.org/abs/2508.18857
Tags: Ajouter un tag
Pas de tags, Soyez le premier à ajouter un tag!
_version_ 1866912725827846144
author Boldi, Paolo
Furia, Flavio
Prezioso, Chiara
Stewart, Ian
author_facet Boldi, Paolo
Furia, Flavio
Prezioso, Chiara
Stewart, Ian
contents Axiomatization of centrality measures often involves proving that something cannot hold by providing a counterexample (i.e., a graph for which that specific centrality index fails to have a given property). In the context of geometric centralities, building such counterexamples requires constructing a graph with specific distance counts between nodes, as expressed by its distance-count matrix. We prove that deciding whether a matrix is the distance-count matrix of a graph is strongly NP-complete. This negative result implies that a brute-force approach to building this kind of counterexample is out of question, and cleverer approaches are required.
format Preprint
id arxiv_https___arxiv_org_abs_2508_18857
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Recognizing Distance-Count Matrices is Difficult
Boldi, Paolo
Furia, Flavio
Prezioso, Chiara
Stewart, Ian
Social and Information Networks
Axiomatization of centrality measures often involves proving that something cannot hold by providing a counterexample (i.e., a graph for which that specific centrality index fails to have a given property). In the context of geometric centralities, building such counterexamples requires constructing a graph with specific distance counts between nodes, as expressed by its distance-count matrix. We prove that deciding whether a matrix is the distance-count matrix of a graph is strongly NP-complete. This negative result implies that a brute-force approach to building this kind of counterexample is out of question, and cleverer approaches are required.
title Recognizing Distance-Count Matrices is Difficult
topic Social and Information Networks
url https://arxiv.org/abs/2508.18857