We have carried out experimental research into implicit representation of large graphs using reduced ordered binary decision diagrams (OBDDs). We experimentally show that for grap...
In this paper, we propose a recursive method for structural learning of directed acyclic graphs (DAGs), in which a problem of structural learning for a large DAG is first decompos...
In recent years, many networks have become available for analysis, including social networks, sensor networks, biological networks, etc. Graph clustering has shown its effectivenes...
We study query processing in large graphs that are fundamental data model underpinning various social networks and Web structures. Given a set of query nodes, we aim to find the g...
Background: Assembling genomic sequences from a set of overlapping reads is one of the most fundamental problems in computational biology. Algorithms addressing the assembly probl...