公开(公告)号：US20210326371A1

公开(公告)日：2021-10-21

申请号：US16849885

申请日：2020-04-15

Applicant: Adobe Inc.

Inventor： Trung Bui ,  Yu Gong ,  Tushar Dublish ,  Sasha Spala ,  Sachin Soni ,  Nicholas Miller ,  Joon Kim ,  Franck Dernoncourt ,  Carl Dockhorn ,  Ajinkya Kale

IPC: G06F16/33 ,  G06N20/00 ,  G06N5/04 ,  G06F40/30

Abstract: Techniques and systems are described for performing semantic text searches. A semantic text-searching solution uses a machine learning system (such as a deep learning system) to determine associations between the semantic meanings of words. These associations are not limited by the spelling, syntax, grammar, or even definition of words. Instead, the associations can be based on the context in which characters, words, and/or phrases are used in relation to one another. In response to detecting a request to locate text within an electronic document associated with a keyword, the semantic text-searching solution can return strings within the document that have matching and/or related semantic meanings or contexts, in addition to exact matches (e.g., string matches) within the document. The semantic text-searching solution can then output an indication of the matching strings.

公开(公告)号：US12130850B2

公开(公告)日：2024-10-29

申请号：US18147960

申请日：2022-12-29

Applicant: Adobe Inc.

Inventor： Trung Bui ,  Yu Gong ,  Tushar Dublish ,  Sasha Spala ,  Sachin Soni ,  Nicholas Miller ,  Joon Kim ,  Franck Dernoncourt ,  Carl Dockhorn ,  Ajinkya Kale

IPC: G06F16/33 ,  G06F40/30 ,  G06N5/04 ,  G06N20/00

CPC classification number: G06F16/3347 ,  G06F40/30 ,  G06N5/04 ,  G06N20/00

Abstract: Techniques and systems are described for performing semantic text searches. A semantic text-searching solution uses a machine learning system (such as a deep learning system) to determine associations between the semantic meanings of words. These associations are not limited by the spelling, syntax, grammar, or even definition of words. Instead, the associations can be based on the context in which characters, words, and/or phrases are used in relation to one another. In response to detecting a request to locate text within an electronic document associated with a keyword, the semantic text-searching solution can return strings within the document that have matching and/or related semantic meanings or contexts, in addition to exact matches (e.g., string matches) within the document. The semantic text-searching solution can then output an indication of the matching strings.

公开(公告)号：US20230133583A1

公开(公告)日：2023-05-04

申请号：US18147960

申请日：2022-12-29

Applicant: Adobe Inc.

Inventor： Trung Bui ,  Yu Gong ,  Tushar Dublish ,  Sasha Spala ,  Sachin Soni ,  Nicholas Miller ,  Joon Kim ,  Franck Dernoncourt ,  Carl Dockhorn ,  Ajinkya Kale

IPC: G06F16/33 ,  G06N20/00 ,  G06F40/30 ,  G06N5/04

Abstract: Techniques and systems are described for performing semantic text searches. A semantic text-searching solution uses a machine learning system (such as a deep learning system) to determine associations between the semantic meanings of words. These associations are not limited by the spelling, syntax, grammar, or even definition of words. Instead, the associations can be based on the context in which characters, words, and/or phrases are used in relation to one another. In response to detecting a request to locate text within an electronic document associated with a keyword, the semantic text-searching solution can return strings within the document that have matching and/or related semantic meanings or contexts, in addition to exact matches (e.g., string matches) within the document. The semantic text-searching solution can then output an indication of the matching strings.

公开(公告)号：US11567981B2

公开(公告)日：2023-01-31

申请号：US16849885

申请日：2020-04-15

Applicant: Adobe Inc.

Inventor： Trung Bui ,  Yu Gong ,  Tushar Dublish ,  Sasha Spala ,  Sachin Soni ,  Nicholas Miller ,  Joon Kim ,  Franck Dernoncourt ,  Carl Dockhorn ,  Ajinkya Kale

IPC: G06F40/30 ,  G06F16/33 ,  G06N20/00 ,  G06N5/04

Abstract: Techniques and systems are described for performing semantic text searches. A semantic text-searching solution uses a machine learning system (such as a deep learning system) to determine associations between the semantic meanings of words. These associations are not limited by the spelling, syntax, grammar, or even definition of words. Instead, the associations can be based on the context in which characters, words, and/or phrases are used in relation to one another. In response to detecting a request to locate text within an electronic document associated with a keyword, the semantic text-searching solution can return strings within the document that have matching and/or related semantic meanings or contexts, in addition to exact matches (e.g., string matches) within the document. The semantic text-searching solution can then output an indication of the matching strings.