In this paper, we develop methods to ‘‘sample’’ a small realistic graph from a large Internet topology. Despite recent activity, modeling and generation of realistic graph...
Background: Biomedical and chemical databases are large and rapidly growing in size. Graphs naturally model such kinds of data. To fully exploit the wealth of information in these...
Abstract. We develop a generic framework for deriving linear-size problem kernels for NP-hard problems on planar graphs. We demonstrate the usefulness of our framework in several c...
Abstract. The vertex cover problem is a classical NP-complete problem for which the best worst-case approximation ratio is 2− o(1). In this paper, we use a collection of simple g...
An algorithm for learning structural patterns given in terms of Attributed Relational Graphs (ARG's) is presented. The algorithm, based on inductive learning methodologies, pr...