We investigate natural extensions of the Continuous Image Graph (CIG) labelling scheme, which is based on the Consecutive Ones Property of matrices. The CIG labelling scheme generalizes tree labelling schemes to many graphs yet remaining as efficient, i.e., adjacency tests run in constant time, the space requirement is constant per node, and testing whether a graph is a CIG is possible in polyn...

In pattern recognition applications, it is useful to represent objects by attributed graphs considering their structural properties. Besides, some graph matching problems need a Common Labelling between vertices of a set of graphs. Computing this Common Labelling is an NP-complete problem. Stateof-the-art algorithms are composed by two steps: in the first, they compute all pairwise labellings a...

Many important algorithms in computational biology and related subjects rely on the ability to extract and to identify sub-graphs of larger graphs; an example is to find common functional structures within Protein Interaction Networks. However, the increasing size of both the graphs to be searched and the target sub-graphs requires the use of large numbers of parallel conventional CPUs. This pa...