Patent attributes
A graph processing system, method and apparatus classifies graphs based on a linearly computable set of features defined as a feature vector adapted for comparison with the feature vectors of other graphs. The features result from graph statistics (“gragnostics”) computable from the edges and vertices of a set of graphs. Graphs are classified based on a multidimensional distance of the resulting feature vectors, and similar graphs are classified according to a distance, or nearest neighbor, of the feature vector corresponding to each graph. Projection of the feature vector onto two dimensions allows visualization of the classification, as similar graphs appear as clusters or groups separated by a relatively shorter distance. Different types or classifications of graphs also appear as other, more distant, clusters. An initial training set defines the classification types, and sampled graphs are evaluated and classified based on the feature vector and nearest neighbors in the training set.
