weg2vec: Event embedding for temporal networks - Archive ouverte HAL Access content directly
Preprints, Working Papers, ... Year :

weg2vec: Event embedding for temporal networks

(1) , (2) , (1)
1
2

Abstract

Network embedding techniques are powerful to capture structural regularities in networks and to identify similarities between their local fabrics. However, conventional network embedding models are developed for static structures, commonly consider nodes only and they are seriously challenged when the network is varying in time. Temporal networks may provide an advantage in the description of real systems, but they code more complex information, which could be effectively represented only by a handful of methods so far. Here, we propose a new method of event embedding of temporal networks, called weg2vec, which builds on temporal and structural similarities of events to learn a low dimensional representation of a temporal network. This projection successfully captures latent structures and similarities between events involving different nodes at different times and provides ways to predict the final outcome of spreading processes unfolding on the temporal structure.

Dates and versions

hal-02388409 , version 1 (01-12-2019)

Identifiers

Cite

Maddalena Torricelli, Márton Karsai, Laetitia Gauvin. weg2vec: Event embedding for temporal networks. 2019. ⟨hal-02388409⟩
65 View
0 Download

Altmetric

Share

Gmail Facebook Twitter LinkedIn More