PORTALE DELLA DIDATTICA

Ricerca CERCA
  KEYWORD

Telecommunication Networks Group

Theses at Politecnico

Machine learning techniques for collective behavior identification

keywords BIG DATA ANALYSIS, COMMUNICATIONS NETWORKS, DARKNET, DATA SCIENCE, GRAPHS, MARKOV CHAINS, MODELLING, SOCIAL NETWORKS, STATISTICS

Reference persons MARCO MELLIA, LUCA VASSIO

External reference persons Idilio Drago (UNITO)

Research Groups SmartData@PoliTO, Telecommunication Networks Group

Thesis type DATA ANALYSIS, MODELLING, NUMERICAL APPROXIMATION

Description In complex systems, there are interactions between entities and we want to characterize and extract the salient types of these interactions. The main applications we are interested to are online social networks like Facebook and Instagram or communication network, like darknets listening to incoming Internet traffic. The student will:
Develop machine learning methodologies to identify coordinated events .
Model the events as a graph and extract emerging patterns.
Make the methodological approach scalable with smart approximations.
Apply these methods to real networks (darknets, social networks), for which we already collected a lot of data

Required skills Modelling, numerical methods, data analysis, python, possibly Big Data (pyspark)

Notes Contact luca.vassio@polito.it


Deadline 16/03/2022      PROPONI LA TUA CANDIDATURA




© Politecnico di Torino
Corso Duca degli Abruzzi, 24 - 10129 Torino, ITALY
Contatti