公开(公告)号：US11232255B2

公开(公告)日：2022-01-25

申请号：US16007632

申请日：2018-06-13

申请人： Adobe Inc.

发明人： Franck Dernoncourt ,  Walter Chang ,  Trung Bui ,  Sean Fitzgerald ,  Sasha Spala ,  Kishore Aradhya ,  Carl Dockhorn

IPC分类号： G06F40/169

摘要： Systems, methods, and non-transitory computer-readable media are disclosed that collect and analyze annotation performance data to generate digital annotations for evaluating and training automatic electronic document annotation models. In particular, in one or more embodiments, the disclosed systems provide electronic documents to annotators based on annotator topic preferences. The disclosed systems then identify digital annotations and annotation performance data such as a time period spent by an annotator in generating digital annotations and annotator responses to digital annotation questions. Furthermore, in one or more embodiments, the disclosed systems utilize the identified digital annotations and the annotation performance data to generate a final set of reliable digital annotations. Additionally, in one or more embodiments, the disclosed systems provide the final set of digital annotations for utilization in training a machine learning model to generate annotations for electronic documents.

公开(公告)号：US11222167B2

公开(公告)日：2022-01-11

申请号：US16721084

申请日：2019-12-19

申请人： Adobe Inc.

发明人： Sebastian Gehrmann ,  Franck Dernoncourt ,  Lidan Wang ,  Carl Dockhorn ,  Yu Gong

IPC分类号： G06F17/00 ,  G06F40/169 ,  G06N20/00 ,  G06F40/284 ,  G06F3/0482 ,  G06F40/253 ,  G06F40/117

摘要： The disclosure describes one or more embodiments of a structured text summary system that generates structured text summaries of digital documents based on an interactive graphical user interface. For example, the structured text summary system can collaborate with users to create structured text summaries of a digital document based on automatically generating document tags corresponding to the digital document, determining segments of the digital document that correspond to a selected document tag, and generating structured text summaries for those document segments.

公开(公告)号：US20210326371A1

公开(公告)日：2021-10-21

申请号：US16849885

申请日：2020-04-15

申请人： Adobe Inc.

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

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

摘要： 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：US20190384807A1

公开(公告)日：2019-12-19

申请号：US16007632

申请日：2018-06-13

申请人： Adobe Inc.

发明人： Franck Dernoncourt ,  Walter Chang ,  Trung Bui ,  Sean Fitzgerald ,  Sasha Spala ,  Kishore Aradhya ,  Carl Dockhorn

IPC分类号： G06F17/24 ,  G06F17/30 ,  G06N3/08 ,  G06N3/04

摘要： Systems, methods, and non-transitory computer-readable media are disclosed that collect and analyze annotation performance data to generate digital annotations for evaluating and training automatic electronic document annotation models. In particular, in one or more embodiments, the disclosed systems provide electronic documents to annotators based on annotator topic preferences. The disclosed systems then identify digital annotations and annotation performance data such as a time period spent by an annotator in generating digital annotations and annotator responses to digital annotation questions. Furthermore, in one or more embodiments, the disclosed systems utilize the identified digital annotations and the annotation performance data to generate a final set of reliable digital annotations. Additionally, in one or more embodiments, the disclosed systems provide the final set of digital annotations for utilization in training a machine learning model to generate annotations for electronic documents.

公开(公告)号：US12130850B2

公开(公告)日：2024-10-29

申请号：US18147960

申请日：2022-12-29

申请人： Adobe Inc.

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

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

CPC分类号： G06F16/3347 ,  G06F40/30 ,  G06N5/04 ,  G06N20/00

摘要： 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

申请人： Adobe Inc.

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

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

摘要： 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

申请人： Adobe Inc.

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

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

摘要： 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：US20210192126A1

公开(公告)日：2021-06-24

申请号：US16721084

申请日：2019-12-19

申请人： Adobe Inc.

发明人： Sebastian Gehrmann ,  Franck Dernoncourt ,  Lidan Wang ,  Carl Dockhorn ,  Yu Gong

IPC分类号： G06F40/169 ,  G06N20/00 ,  G06F40/117 ,  G06F3/0482 ,  G06F40/253 ,  G06F40/284

摘要： The disclosure describes one or more embodiments of a structured text summary system that generates structured text summaries of digital documents based on an interactive graphical user interface. For example, the structured text summary system can collaborate with users to create structured text summaries of a digital document based on automatically generating document tags corresponding to the digital document, determining segments of the digital document that correspond to a selected document tag, and generating structured text summaries for those document segments.