Temporal network compression via network hashing - Archive ouverte HAL Accéder directement au contenu
Pré-Publication, Document De Travail Année : 2023

Temporal network compression via network hashing

Résumé

Pairwise temporal interactions between entities can be represented as temporal networks, which code the propagation of processes such as epidemic spreading or information cascades, evolving on top of them. The largest outcome of these processes is directly linked to the structure of the underlying network. Indeed, a node of a network at given time cannot affect more nodes in the future than it can reach via time-respecting paths. This set of nodes reachable from a source defines an out-component, which identification is costly. In this paper, we propose an efficient matrix algorithm to tackle this issue and show that it outperforms other state-of-the-art methods. Secondly, we propose a hashing framework to coarsen large temporal networks into smaller proxies on which out-components are easier to estimate, and then recombined to obtain the initial components. Our graph hashing solution has implications in privacy respecting representation of temporal networks.
Fichier principal
Vignette du fichier
2307.04890.pdf (1.08 Mo) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)

Dates et versions

hal-04228037 , version 1 (04-10-2023)

Licence

Paternité

Identifiants

Citer

Rémi Vaudaine, Pierre Borgnat, Paulo Gonçalves, Rémi Gribonval, Márton Karsai. Temporal network compression via network hashing. 2023. ⟨hal-04228037⟩
26 Consultations
22 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More