  Recent works explore social characteristics of nodes to improve message
delivery rate in Delay Tolerant Networks (DTN). This work uses machine learning
techniques to create node groups organized by common interests. Messages are
sent to target groups, and from there to the final destination. Simulation
results using The ONE simulator show that the larger the group size the higher
the message delivery rate, that reaches 100% in some cases. The paper also
presents results related to the groups of interest such as message delivery
rat, delivery delay and an average number of hops to deliver messages. The
overall results indicate that group-based routing is a promising research
filed.
