In recent years, researchers in graph mining have been exploring linear paths as well as subgraphs as pattern languages. In this paper, we are investigating the middle ground betw...
We present how to efficiently mine a set of directed acyclic graphs (DAGs) for unconnected, both multi- or single-rooted, and induced fragments. With a new canonical form that is ...
We present an algorithm for mining tree-shaped patterns in a large graph. Novel about our class of patterns is that they can contain constants, and can contain existential nodes w...
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...