—Social network methods are frequently used to analyze networks derived from Open Source Project communication and collaboration data. Such studies typically discover patterns in...
Roozbeh Nia, Christian Bird, Premkumar T. Devanbu,...
As advances in technology allow for the collection, storage, and analysis of vast amounts of data, the task of screening and assessing the significance of discovered patterns is b...
Adam Kirsch, Michael Mitzenmacher, Andrea Pietraca...
By analyzing the similarities between bit streams coming from a network of motion detectors, we can recover the network geometry and discover structure in the human behavior being...
Christopher Richard Wren, David C. Minnen, Sriniva...
When mining a large database, the number of patterns discovered can easily exceed the capabilities of a human user to identify interesting results. To address this problem, variou...
This paper introduces LDA-G, a scalable Bayesian approach to finding latent group structures in large real-world graph data. Existing Bayesian approaches for group discovery (suc...