公开(公告)号：US12190621B2

公开(公告)日：2025-01-07

申请号：US17653414

申请日：2022-03-03

Applicant: Adobe Inc.

Inventor： Debraj Debashish Basu ,  Shankar Venkitachalam ,  Vinh Khuc ,  Deepak Pai

IPC: G06F17/00 ,  G06F40/295 ,  G06N20/00 ,  G06V30/19 ,  G06V30/416

Abstract: The present disclosure relates to systems, methods, and non-transitory computer readable media that utilize intelligent contextual bias weights for informing keyphrase relevance models to extract keyphrases. For example, the disclosed systems generate a graph from a digital document by mapping words from the digital document to nodes of the graph. In addition, the disclosed systems determine named entity bias weights for the nodes of the graph utilizing frequencies with which the words corresponding to the nodes appear within named entities identified from the digital document. Moreover, the disclosed systems generate a keyphrase summary for the digital document utilizing the graph and a machine learning model biased according to the named entity bias weights for the nodes of the graph.

公开(公告)号：US20230282018A1

公开(公告)日：2023-09-07

申请号：US17653414

申请日：2022-03-03

Applicant: Adobe Inc.

Inventor： Debraj Debashish Basu ,  Shankar Venkitachalam ,  Vinh Khuc ,  Deepak Pai

IPC: G06V30/416 ,  G06V30/19 ,  G06F40/295 ,  G06N20/00

CPC classification number: G06V30/416 ,  G06V30/19127 ,  G06V30/19113 ,  G06F40/295 ,  G06N20/00

Abstract: The present disclosure relates to systems, methods, and non-transitory computer readable media that utilize intelligent contextual bias weights for informing keyphrase relevance models to extract keyphrases. For example, the disclosed systems generate a graph from a digital document by mapping words from the digital document to nodes of the graph. In addition, the disclosed systems determine named entity bias weights for the nodes of the graph utilizing frequencies with which the words corresponding to the nodes appear within named entities identified from the digital document. Moreover, the disclosed systems generate a keyphrase summary for the digital document utilizing the graph and a machine learning model biased according to the named entity bias weights for the nodes of the graph.