Efficient Probabilistic Truss Indexing on Uncertain Graphs

Networks in many real-world applications come with an inherent uncertainty in their structure, due to e.g., noisy measurements, inference and prediction models, or for privacy purposes. Modeling and analyzing uncertain graphs has attracted a great deal of attention. Among the various graph analytic tasks studied, the extraction of dense substructures, such as cores or trusses, has a central role.