Graphs are being increasingly used to model a wide range of scientific data. Such widespread usage of graphs has generated considerable interest in mining patterns from graph datab...
Discriminative subgraphs are widely used to define the feature space for graph classification in large graph databases. Several scalable approaches have been proposed to mine disc...
Existing graph mining algorithms typically assume that databases are relatively static and can fit into the main memory. Mining of subgraphs in a dynamic environment is currently ...
New graph structures where node labels are members of hierarchically organized ontologies or taxonomies have become commonplace in different domains, e.g., life sciences. It is a ...
Graph data are subject to uncertainties in many applications due to incompleteness and imprecision of data. Mining uncertain graph data is semantically different from and computat...