Tipo di tesi
Tesi di laurea magistrale
Titolo
Fast Similarity for Large Attributed Networks
Corso di studi
INFORMATICA
Parole chiave
- attributed networks
- graph
- graph algorithms
- similarity
- social network analysis
Data inizio appello
03/12/2021
Consultabilità
Non consultabile
Data di rilascio
03/12/2091
Riassunto (Italiano)
Attributed networks store multiple values in their nodes, whose informative content is not always related to the structural content provided by the networks’ links.
While the literature has extensively studied many methods to perform clustering, community detection, and graph and pattern mining in these networks, less effort has been devoted to investigate similarity as a main goal (except for the similarity inside clusters and communities).
In this thesis, we exploit the attributes of the nodes found along in fixed length paths to define signatures that enrich the attribute content.
We provide experiments to motivate the significance of signatures on real-world networks with up to 30 million edges, fast algorithms to build sampled signatures for large graphs and discuss some applications such as node similarity, role similarity, and link prediction, for which our (sampled) signatures provide interesting experimental figures.
