Archaeology of random recursive dags and Cooper-Frieze random networks
This addresses the challenge of root identification in network analysis, with incremental improvements in theoretical guarantees for specific random graph models.
The paper tackles the problem of locating the root vertex in large growing networks, proving that confidence sets of size independent of the number of vertices can contain the root with high probability in models like uniform random recursive dags and Cooper-Frieze random graphs.
We study the problem of finding the root vertex in large growing networks. We prove that it is possible to construct confidence sets of size independent of the number of vertices in the network that contain the root vertex with high probability in various models of random networks. The models include uniform random recursive dags and uniform Cooper-Frieze random graphs.