Skip to Main content Skip to Navigation
Theses

Prédiction d'interactions dans les flots de liens. Combiner les caractéristiques structurelles et temporelles

Abstract : The link stream formalism represent an approach allowing to capture the system dynamic while providing a framework to understand the system's behavior. A link stream is a sequence of triplet (t,u,v) indicating that an interaction occurred between u and v at time t. The importance of the system's dynamic during the prediction places it at the crossroads of link prediction in graphs and time series prediction. We will explore several formalizations of the problem of prediction in link streams. In the following we will study the activity prediction, that is to say predicting the number of interactions occurring in the future between each pair of nodes during a given period. We introduce the protocol, allowing to combine the data characteristics to predict the activity. We study the behavior of our protocol during several experiments on four datasets et evaluate the prediction quality. We will look at how the introduction of pair of nodes classes allows to preserve the link diversity in the prediction while improving the prediction. Our goal is to define a general prediction framework allowing in-depth studies of the relationship between temporal and structural characteristics in prediction tasks.
Complete list of metadatas

Cited literature [66 references]  Display  Hide  Download

https://tel.archives-ouvertes.fr/tel-02481333
Contributor : Abes Star :  Contact
Submitted on : Monday, February 17, 2020 - 1:52:11 PM
Last modification on : Monday, June 15, 2020 - 11:48:56 AM
Long-term archiving on: : Monday, May 18, 2020 - 4:12:27 PM

File

ARNOUX_Thibaud_these_2018.pdf
Version validated by the jury (STAR)

Identifiers

  • HAL Id : tel-02481333, version 1

Citation

Thibaud Arnoux. Prédiction d'interactions dans les flots de liens. Combiner les caractéristiques structurelles et temporelles. Réseaux sociaux et d'information [cs.SI]. Sorbonne Université, 2018. Français. ⟨NNT : 2018SORUS229⟩. ⟨tel-02481333⟩

Share

Metrics

Record views

115

Files downloads

54