Users of social networking services can connect with each other by forming communities for online interaction. Yet as the number of communities hosted by such websites grows over ...
We propose two approximation algorithms for identifying communities in dynamic social networks. Communities are intuitively characterized as "unusually densely knit" sub...
We propose a new unsupervised learning technique for extracting information from large text collections. We model documents as if they were generated by a two-stage stochastic pro...
Mark Steyvers, Padhraic Smyth, Michal Rosen-Zvi, T...
Online social networks are now a popular way for users to connect, express themselves, and share content. Users in today's online social networks often post a profile, consis...
Alan Mislove, Bimal Viswanath, P. Krishna Gummadi,...
Abstract. Recently, we have proposed a novel method for the compression of time series based on mathematical models that explore dependencies between different time series. This r...