Three-hop distance estimation in social graphs

In this paper, we study a 3-hop approach to distance estimation that uses two intermediate landmarks, where each landmark only stores distances to vertices in its local neighborhood and to the other landmarks. We show how to suitably represent and compress the distance data stored for each landmark, for the 2-hop and 3-hop case. Overall, we find that 3-hop methods achieve modest but promising improvement in some cases, while being comparable or slightly worse than 2-hop methods in others. Furthermore, our light compression schemes improve the practical applicability of both the 2-hop and 3-hop methods.