ARNOUX Thibaud

PhD graduated
Team : ComplexNetworks
Departure date : 12/25/2018

Supervision : Matthieu LATAPY

Co-supervision : TABOURIER Lionel

Predicting interactions in link streams - Combining structural and temporal features

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.

Defence : 06/29/2018

Jury members :

David Chavalarias [Rapporteur]
Christophe Crespelle [Rapporteur]
Rushed Kanawati
Pierre Borgnat
Anne Fladenmuller
Matthieu Latapy
Lionel Tabourier

Departure date : 12/25/2018

2017-2019 Publications