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Temporal network compression via network hashing
Title / Series / Name
Publication Volume
Publication Issue
Pages
Editors
Keywords
Graph hashing
Out-component calculation
Streaming matrix algorithms
Temporal networks
Multidisciplinary
Computer Networks and Communications
Computational Mathematics
Out-component calculation
Streaming matrix algorithms
Temporal networks
Multidisciplinary
Computer Networks and Communications
Computational Mathematics
URI
https://hdl.handle.net/20.500.14018/26510
Abstract
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 a 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 more easily estimated, and then recombined to obtain the initial components. Our graph hashing solution has implications in privacy respecting representation of temporal networks.
Topic
Publisher
Place of Publication
Type
Journal article
Date
2024-01-17
Language
ISBN
Identifiers
10.1007/s41109-023-00609-9