CPC G06N 3/04 (2013.01) [G06N 3/08 (2013.01)] | 16 Claims |
1. A method for extracting human-interpretable entity profiles from a text-labeled data graph of a system comprised of entities, the method comprising:
constructing neural network layers, wherein the data graph comprises nodes representing the entities and edges between the nodes representing links between the entities, wherein a plurality of text is respectively associated with the corresponding edges, and wherein the neural network layers are constructed such that each of the edges between a pair of the nodes is modeled as a function of the associated text and cluster representations of the pair of the nodes,
for each one of the pair of nodes, performing machine learning to learn a tensor to capture patterns among the associated text and the pair of nodes, and
extracting the human-interpretable entity profiles from the tensor.
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