公开(公告)号：US11783008B2

公开(公告)日：2023-10-10

申请号：US17091403

申请日：2020-11-06

Applicant: Adobe Inc.

Inventor： Rajiv Jain ,  Varun Manjunatha ,  Joseph Barrow ,  Vlad Ion Morariu ,  Franck Dernoncourt ,  Sasha Spala ,  Nicholas Miller

IPC: G06F18/214 ,  G06F40/30 ,  G06F40/117 ,  G06V30/413 ,  G06F18/21 ,  G06F18/2415 ,  G06F16/33

CPC classification number: G06F18/2148 ,  G06F18/217 ,  G06F18/2415 ,  G06F40/117 ,  G06F40/30 ,  G06V30/413 ,  G06F16/33 ,  G06V2201/10

Abstract: Certain embodiments involve using a machine-learning tool to generate metadata identifying segments and topics for text within a document. For instance, in some embodiments, a text processing system obtains input text and applies a segmentation-and-labeling model to the input text. The segmentation-and-labeling model is trained to generate a predicted segment for the input text using a segmentation network. The segmentation-and-labeling model is also trained to generate a topic for the predicted segment using a pooling network of the model to the predicted segment. The output of the model is usable for generating metadata identifying the predicted segment and the associated topic.

公开(公告)号：US12147499B2

公开(公告)日：2024-11-19

申请号：US18242075

申请日：2023-09-05

Applicant: Adobe Inc.

Inventor： Rajiv Jain ,  Varun Manjunatha ,  Joseph Barrow ,  Vlad Ion Morariu ,  Franck Dernoncourt ,  Sasha Spala ,  Nicholas Miller

IPC: G06F18/214 ,  G06F16/33 ,  G06F18/21 ,  G06F18/2415 ,  G06F40/117 ,  G06F40/30 ,  G06V30/413

Abstract: Certain embodiments involve using a machine-learning tool to generate metadata identifying segments and topics for text within a document. For instance, in some embodiments, a text processing system obtains input text and applies a segmentation-and-labeling model to the input text. The segmentation-and-labeling model is trained to generate a predicted segment for the input text using a segmentation network. The segmentation-and-labeling model is also trained to generate a topic for the predicted segment using a pooling network of the model to the predicted segment. The output of the model is usable for generating metadata identifying the predicted segment and the associated topic.

公开(公告)号：US20230409672A1

公开(公告)日：2023-12-21

申请号：US18242075

申请日：2023-09-05

Applicant: Adobe Inc.

Inventor： Rajiv Jain ,  Varun Manjunatha ,  Joseph Barrow ,  Vlad Ion Morariu ,  Franck Dernoncourt ,  Sasha Spala ,  Nicholas Miller

IPC: G06F18/214 ,  G06F40/30 ,  G06F40/117 ,  G06V30/413 ,  G06F18/21 ,  G06F18/2415

CPC classification number: G06F18/2148 ,  G06F40/30 ,  G06F40/117 ,  G06V30/413 ,  G06F18/217 ,  G06F18/2415 ,  G06V2201/10 ,  G06F16/33

Abstract: Certain embodiments involve using a machine-learning tool to generate metadata identifying segments and topics for text within a document. For instance, in some embodiments, a text processing system obtains input text and applies a segmentation-and-labeling model to the input text. The segmentation-and-labeling model is trained to generate a predicted segment for the input text using a segmentation network. The segmentation-and-labeling model is also trained to generate a topic for the predicted segment using a pooling network of the model to the predicted segment. The output of the model is usable for generating metadata identifying the predicted segment and the associated topic.

公开(公告)号：US20230033114A1

公开(公告)日：2023-02-02

申请号：US17384136

申请日：2021-07-23

Applicant: ADOBE INC.

Inventor： Joseph Barrow ,  Rajiv Bhawanji Jain ,  Nedim Lipka ,  Vlad Ion Morariu ,  Franck Dernoncourt ,  Varun Manjunatha

IPC: G06F16/35 ,  G06F40/169 ,  G06F40/289 ,  G06N3/04

Abstract: Systems and methods for natural language processing are described. One or more embodiments of the present disclosure identify a claim from a document, wherein the claim corresponds to a topic, create a graph comprising a plurality of nodes having a plurality of node types and a plurality of edges having a plurality of edge types, wherein one of the nodes represents the claim, and wherein each of the edges represents a relationship between a corresponding pair of the nodes, encode the claim based on the graph using a graph convolutional network (GCN) to obtain an encoded claim, classify the claim by decoding the encoded claim to obtain a stance label that indicates a stance of the claim towards the topic, and transmit information indicating a viewpoint of the document towards the topic based on the stance label.

公开(公告)号：US20220147770A1

公开(公告)日：2022-05-12

申请号：US17091403

申请日：2020-11-06

Applicant: Adobe Inc.

Inventor： Rajiv Jain ,  Varun Ion Manjunatha ,  Joseph Barrow ,  Vlad Ion Moraniu ,  Franck Dernoncourt ,  Sasha Spala ,  Nicholas Miller

IPC: G06K9/62 ,  G06K9/00 ,  G06F40/30 ,  G06F40/117

Abstract: Certain embodiments involve using a machine-learning tool to generate metadata identifying segments and topics for text within a document. For instance, in some embodiments, a text processing system obtains input text and applies a segmentation-and-labeling model to the input text. The segmentation-and-labeling model is trained to generate a predicted segment for the input text using a segmentation network. The segmentation-and-labeling model is also trained to generate a topic for the predicted segment using a pooling network of the model to the predicted segment. The output of the model is usable for generating metadata identifying the predicted segment and the associated topic.

公开(公告)号：US20240419921A1

公开(公告)日：2024-12-19

申请号：US18336380

申请日：2023-06-16

Applicant: Adobe Inc.

Inventor： Joseph Barrow ,  Jennifer Healey ,  Franck Dernoncourt ,  Ani Nenkova ,  Vlad Morariu ,  Rajiv Jain ,  Nedim Lipka

IPC: G06F40/40 ,  G06F40/205 ,  G06V30/19

Abstract: This disclosure describes one or more implementations of systems, non-transitory computer-readable media, and methods that extract viewpoints from content for syntopical reading using an efficient claim-relation graph construction approach. For example, the disclosed systems utilize sentence transformers with claims from content to embed the claims within a metric space (as claim nodes). Furthermore, in some embodiments, the disclosed systems generate a claim relation graph for the claims by utilizing approximate nearest neighbor searches to determine relational edges between a claim node and the claim node's approximate nearest neighbors. Moreover, in some implementations, the disclosed systems utilize the claim relation graph with an edge weighted graph neural network to determine stance labels during extraction of viewpoints (e.g., stance, aspect, and topic) for the claims. Additionally, in one or more instances, the disclosed systems utilize the extracted viewpoints in content retrieval applications (e.g., viewpoint ranked search results and/or socially contextualized claims).

公开(公告)号：US12038962B2

公开(公告)日：2024-07-16

申请号：US17384136

申请日：2021-07-23

Applicant: ADOBE INC.

Inventor： Joseph Barrow ,  Rajiv Bhawanji Jain ,  Nedim Lipka ,  Vlad Ion Morariu ,  Franck Dernoncourt ,  Varun Manjunatha

IPC: G06F16/35 ,  G06F40/169 ,  G06F40/289

CPC classification number: G06F16/358 ,  G06F40/169 ,  G06F40/289

Abstract: Systems and methods for natural language processing are described. One or more embodiments of the present disclosure identify a claim from a document, wherein the claim corresponds to a topic, create a graph comprising a plurality of nodes having a plurality of node types and a plurality of edges having a plurality of edge types, wherein one of the nodes represents the claim, and wherein each of the edges represents a relationship between a corresponding pair of the nodes, encode the claim based on the graph using a graph convolutional network (GCN) to obtain an encoded claim, classify the claim by decoding the encoded claim to obtain a stance label that indicates a stance of the claim towards the topic, and transmit information indicating a viewpoint of the document towards the topic based on the stance label.