Gragnostics rendering
AssigneeTwo Six Labs, LLC
InventorRobert P. Gove, JR.
Life of this patent
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AssigneeTwo Six Labs, LLC
InventorRobert P. Gove, JR.
Estimating the term…
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.
In an analytics environment having graph data responsive to rendering for visual recognition and comparison of statistical trends defined in a plurality of graphs, a scalable method of visualized graph data, comprising:
A computerized device for visualizing graph data comprising:
A computer program product on a non-transitory computer readable storage medium having instructions that, when executed by a processor, perform a method of rendering visualized graph data, the method comprising:
Dependencies are inferred from the claim text.