State-of-the-art techniques for probability sampling of users of online social networks (OSNs) are based on random walks on a single social relation. While powerful, these methods ...
Minas Gjoka, Carter T. Butts, Maciej Kurant, Athin...
Abstract—We study the performance of several search algorithms on unstructured peer-to-peer networks, both using classic search algorithms such as flooding and random walk, as w...
We present a framework for approximating random-walk based probability distributions over Web pages using graph aggregation. We (1) partition the Web's graph into classes of ...
Andrei Z. Broder, Ronny Lempel, Farzin Maghoul, Ja...
We consider the problem of online sublinear expander reconstruction and its relation to random walks in “noisy” expanders. Given access to an adjacency list representation of ...
This paper studies how to incorporate side information (such as users’ feedback) in measuring node proximity on large graphs. Our method (ProSIN) is motivated by the well-studie...