公开(公告)号：US20210248458A1

公开(公告)日：2021-08-12

申请号：US16785477

申请日：2020-02-07

Applicant: Florence ROBERT-RÉGOL ,  Yingxue ZHANG ,  Mark COATES

Inventor： Florence ROBERT-RÉGOL ,  Yingxue ZHANG ,  Mark COATES

IPC: G06N3/08 ,  G06F16/901 ,  G06N3/04

Abstract: Method and system for processing an attributed graph that comprises a training dataset of labelled nodes and an unlabeled dataset of unlabeled nodes. The method and system includes selecting, using logistic regression, which candidate node from a plurality of possible candidate nodes included in the unlabeled dataset will minimize a risk if that candidate node is added to the training dataset; obtaining a label for the selected candidate node from a classification resource; and adding the selected candidate node and the obtained label to the training dataset as a labelled node to provide an enhanced training dataset.

公开(公告)号：US20210034737A1

公开(公告)日：2021-02-04

申请号：US16944073

申请日：2020-07-30

Applicant: Sakif Hossain KHAN ,  Yingxue ZHANG ,  Florence ROBERT-RÉGOL ,  Mark COATES ,  Liheng MA

Inventor： Sakif Hossain KHAN ,  Yingxue ZHANG ,  Florence ROBERT-RÉGOL ,  Mark COATES ,  Liheng MA

IPC: G06F21/55 ,  G06N3/08 ,  G06N3/04

Abstract: Method and system for detecting potentially perturbed nodes in a graph that comprises potentially perturbed nodes and clean nodes, comprising: calculating, for each of a plurality of nodes of the graph, a discrepancy value in respect of the node, wherein the discrepancy value for each node indicates a statistical discrepancy for classification probabilities associated with the node and classification probabilities associated with neighbouring nodes; fitting a statistical distribution for the discrepancy values for the clean nodes; determining a detection threshold for potentially perturbed nodes based on the statistical distribution; and identifying nodes having a discrepancy value greater than the detection threshold as potentially perturbed nodes.