Sas Institute Inc.

James Byron Morris

Nicholas Akbar Ablitt

Joseph P Forte

The computing device trains a first model on a first data set using a first graph to predict relevant links between a plurality of nodes. The computing device obtains the first data set or a second data set associated with the plurality of nodes. The computing device determines the one or more features for the one or more links between the plurality of nodes, applies the trained first model to the one or more links between the plurality of nodes, outputs the relevant links and non-relevant links of the one or more links between the plurality of nodes, removes the non-relevant links between the plurality of nodes, connects each node of the plurality of nodes with the relevant links to generate one or more first sets of networks, and outputs the one or more first sets of generated networks.

Method and system for predicting relevant network relationships

The computing device trains a first model on a first data set using a first graph to predict relevant links between a plurality of nodes. The computing device applies the trained first model to the one or more links between the plurality of nodes from a first node, iteratively connects each node to the one or more first sets of generated networks for each of the relevant links until the relevant links for connection to the plurality of nodes are not present, and outputs the one or more first sets of generated networks. The computing device also applies the trained first model to the one or more links between the plurality of nodes, removes the non-relevant links, connects each node of the plurality of nodes with the relevant links to generate one or more second sets of networks, and outputs the one or more second sets of generated networks.

Growing community of inventors

Raleigh, NC, United States of America

James Byron Morris