ETD

Archivio digitale delle tesi discusse presso l'Università di Pisa

Tesi etd-06282018-053216


Tipo di tesi
Tesi di laurea magistrale
Autore
PEDRESCHI, NICOLA
URN
etd-06282018-053216
Titolo
Community detection in dynamic networks: phase transitions and online inference
Dipartimento
FISICA
Corso di studi
FISICA
Relatori
relatore Prof. Lillo, Fabrizio
relatore Prof. Mannella, Riccardo
Parole chiave
  • statistical physics
  • network science
  • complex systems
  • community detection
  • belief propagation
  • temporal networks
Data inizio appello
19/07/2018
Consultabilità
Completa
Riassunto
In this thesis I propose a model, and associated algorithms, for on-line community detection in dynamic networks. I test the performance of the algorithms on synthetic networks generated by the Dynamic Stochastic Block model, focusing on the question whether we can, at every moment in the network's dynamics, infer its organization in communities and learn the unknown parameters that were used to generate it, based on the only knowledge of the connections between pairs of nodes. We extend the analysis studied in literature on the phase diagrams of Belief Propagation algorithms for community detection, using the cavity method of statistical physics to evaluate the phase diagram of our and existing models.
File