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...
—This work introduces a link-based covariance measure between the nodes of a weighted directed graph where a cost is associated to each arc. To this end, a probability distributi...
Background: Automated extraction of protein-protein interactions (PPI) is an important and widely studied task in biomedical text mining. We propose a graph kernel based approach ...
An important problem in the area of homeland security is to identify abnormal or suspicious entities in large datasets. Although there are methods from data mining and social netwo...
Archival storage of sensor data is necessary for applications that query, mine, and analyze such data for interesting features and trends. We argue that existing storage systems a...
Peter Desnoyers, Deepak Ganesan, Prashant J. Sheno...