—In this paper, we propose a Bayesian-inference based recommendation system for online social networks. In our system, users share their content ratings with friends. The rating ...
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...
In this paper, we propose examining the participants in various meetings or communications within a social network, and using sequential inference based on these participant lists...
Online social networks have become very popular in recent years and their number of users is already measured in many hundreds of millions. For various commercial and sociological...
In the blog world, bloggers produce information, establish relationships with other bloggers in order to exchange information, and form a blog network, an online social network. I...