Graphs capture the essential elements of many problems broadly defined as searching or categorizing. With the rapid increase of data volumes from sensors, many application discipl...
An increasing number of tasks require people to explore, navigate and search extremely complex data sets visualized as graphs. Examples include electrical and telecommunication ne...
Nelson Wong, M. Sheelagh T. Carpendale, Saul Green...
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 fun...
Currently, a large amount of data can be best represented as graphs, e.g., social networks, protein interaction networks, etc. The analysis of these networks is an urgent research ...
—In this paper we propose a symbol spotting technique through hashing the shape descriptors of graph paths (Hamiltonian paths). Complex graphical structures in line drawings can ...