公开(公告)号：US11467857B2

公开(公告)日：2022-10-11

申请号：US17069637

申请日：2020-10-13

Applicant: Adobe Inc.

Inventor： Oliver Brdiczka ,  Robert Alley ,  Kyoung Tak Kim ,  Kevin Gary Smith ,  Aliakbar Darabi

IPC: G06F11/34 ,  G06F9/451 ,  G06T11/00 ,  G06N20/00

Abstract: The present disclosure describes systems, non-transitory computer-readable media, and methods that intelligently sense digital user context across client devices applications utilizing a dynamic sensor graph framework and then utilize a persistent context store to generate flexible digital recommendations across digital applications. In one or more embodiments, the disclosed systems utilize triggers to select and activate one or more sensor graphs. These sensor graphs can include software sensors arranged according to an architecture of dependencies and subject to various constraints. The underlying architecture of dependencies and constraints in each sensor graph allows the disclosed systems to avoid race-conditions in persisting actionable user-context based signals, verify the validity of sensor output through the sensor graph, generate user-context based recommendations across multiple related applications, and accommodate a specific latency/refresh rate of context values.

公开(公告)号：US20220413881A1

公开(公告)日：2022-12-29

申请号：US17823811

申请日：2022-08-31

Applicant: Adobe Inc.

Inventor： Oliver Brdiczka ,  Robert Alley ,  Kyoung Tak Kim ,  Kevin Gary Smith ,  Aliakbar Darabi

IPC: G06F9/451 ,  G06T11/00 ,  G06F11/34 ,  G06N20/00

Abstract: The present disclosure describes systems, non-transitory computer-readable media, and methods that intelligently sense digital user context across client devices applications utilizing a dynamic sensor graph framework and then utilize a persistent context store to generate flexible digital recommendations across digital applications. In one or more embodiments, the disclosed systems utilize triggers to select and activate one or more sensor graphs. These sensor graphs can include software sensors arranged according to an architecture of dependencies and subject to various constraints. The underlying architecture of dependencies and constraints in each sensor graph allows the disclosed systems to avoid race-conditions in persisting actionable user-context based signals, verify the validity of sensor output through the sensor graph, generate user-context based recommendations across multiple related applications, and accommodate a specific latency/refresh rate of context values.

公开(公告)号：US20220310084A1

公开(公告)日：2022-09-29

申请号：US17211392

申请日：2021-03-24

Applicant: ADOBE INC.

Inventor： OLIVER BRDICZKA ,  Kyoung Tak Kim ,  Charat Maheshwari

IPC: G10L15/22 ,  G10L15/18 ,  G10L15/06 ,  G06F16/242 ,  G06F16/2453 ,  G06F16/248

Abstract: The present disclosure describes systems and methods for extensible search, content, and dialog management. Embodiments of the present disclosure provide a dialog system with a trained intent recognition model (e.g., a deep learning model) to receive and understand a natural language query from a user. In cases where intent is not identified for a received query, the dialog system generates one or more candidate responses that may be refined (e.g., using human-in-the-loop curation) to generate a response. The intent recognition model may be updated (e.g., retrained) the accordingly. Upon receiving a subsequent query with similar intent, the dialog system may identify the intent using the updated intent recognition model.

公开(公告)号：US20220113996A1

公开(公告)日：2022-04-14

申请号：US17069637

申请日：2020-10-13

Applicant: Adobe Inc.

Inventor： Oliver Brdiczka ,  Robert Alley ,  Kyoung Tak Kim ,  Kevin Gary Smith ,  Aliakbar Darabi

IPC: G06F9/451 ,  G06N20/00 ,  G06F11/34 ,  G06T11/00

Abstract: The present disclosure describes systems, non-transitory computer-readable media, and methods that intelligently sense digital user context across client devices applications utilizing a dynamic sensor graph framework and then utilize a persistent context store to generate flexible digital recommendations across digital applications. In one or more embodiments, the disclosed systems utilize triggers to select and activate one or more sensor graphs. These sensor graphs can include software sensors arranged according to an architecture of dependencies and subject to various constraints. The underlying architecture of dependencies and constraints in each sensor graph allows the disclosed systems to avoid race-conditions in persisting actionable user-context based signals, verify the validity of sensor output through the sensor graph, generate user-context based recommendations across multiple related applications, and accommodate a specific latency/refresh rate of context values.

公开(公告)号：US12159151B2

公开(公告)日：2024-12-03

申请号：US17823811

申请日：2022-08-31

Applicant: Adobe Inc.

Inventor： Oliver Brdiczka ,  Robert Alley ,  Kyoung Tak Kim ,  Kevin Gary Smith ,  Aliakbar Darabi

IPC: G06F9/451 ,  G06F11/34 ,  G06N20/00 ,  G06T11/00

Abstract: The present disclosure describes systems, non-transitory computer-readable media, and methods that intelligently sense digital user context across client devices applications utilizing a dynamic sensor graph framework and then utilize a persistent context store to generate flexible digital recommendations across digital applications. In one or more embodiments, the disclosed systems utilize triggers to select and activate one or more sensor graphs. These sensor graphs can include software sensors arranged according to an architecture of dependencies and subject to various constraints. The underlying architecture of dependencies and constraints in each sensor graph allows the disclosed systems to avoid race-conditions in persisting actionable user-context based signals, verify the validity of sensor output through the sensor graph, generate user-context based recommendations across multiple related applications, and accommodate a specific latency/refresh rate of context values.

公开(公告)号：US12061916B2

公开(公告)日：2024-08-13

申请号：US17657477

申请日：2022-03-31

Applicant: Adobe Inc.

Inventor： Oliver Brdiczka ,  Thomas Donahue ,  Neha Gautam ,  Kyoung Tak Kim ,  Jakub Plichta ,  Keenan Villani-Holland ,  Gabriel Palma Coelho ,  Chun Hao Wang ,  Allan Young

IPC: G06F9/451

CPC classification number: G06F9/451

Abstract: The present disclosure relates to systems, methods, and non-transitory computer-readable media that recommends application features of software applications based on in-application behavior and provides the recommendations within a dynamically updating graphical user interface. For instance, in one or more embodiments, the disclosed systems utilize behavioral signals reflecting the behavior of a user with respect to one or more software applications to recommend application features of the software application(s). For instance, in some cases, the disclosed systems recommend an application feature related to recent activity user, an application feature from a curated recommendation list that has yet to be viewed, and/or an application feature determined via machine learning. In some embodiments, the disclosed systems dynamically update a graphical user interface of a client device in real time as the user utilizes the client device to access and navigate the software application(s) to display these recommendations.

公开(公告)号：US11948566B2

公开(公告)日：2024-04-02

申请号：US17211392

申请日：2021-03-24

Applicant: ADOBE INC.

Inventor： Oliver Brdiczka ,  Kyoung Tak Kim ,  Charat Maheshwari

IPC: G10L15/22 ,  G06F16/242 ,  G06F16/2453 ,  G06F16/248 ,  G10L15/06 ,  G10L15/18

CPC classification number: G10L15/22 ,  G06F16/243 ,  G06F16/24539 ,  G06F16/248 ,  G10L15/063 ,  G10L15/18 ,  G10L2015/227

Abstract: The present disclosure describes systems and methods for extensible search, content, and dialog management. Embodiments of the present disclosure provide a dialog system with a trained intent recognition model (e.g., a deep learning model) to receive and understand a natural language query from a user. In cases where intent is not identified for a received query, the dialog system generates one or more candidate responses that may be refined (e.g., using human-in-the-loop curation) to generate a response. The intent recognition model may be updated (e.g., retrained) the accordingly. Upon receiving a subsequent query with similar intent, the dialog system may identify the intent using the updated intent recognition model.

公开(公告)号：US20230315491A1

公开(公告)日：2023-10-05

申请号：US17657477

申请日：2022-03-31

Applicant: Adobe Inc.

Inventor： Oliver Brdiczka ,  Thomas Donahue ,  Neha Gautam ,  Kyoung Tak Kim ,  Jakub Plichta ,  Keenan Villani-Holland ,  Gabriel Palma Coelho ,  Chun Hao Wang ,  Allan Young

IPC: G06F9/451

CPC classification number: G06F9/451

Abstract: The present disclosure relates to systems, methods, and non-transitory computer-readable media that recommends application features of software applications based on in-application behavior and provides the recommendations within a dynamically updating graphical user interface. For instance, in one or more embodiments, the disclosed systems utilize behavioral signals reflecting the behavior of a user with respect to one or more software applications to recommend application features of the software application(s). For instance, in some cases, the disclosed systems recommend an application feature related to recent activity user, an application feature from a curated recommendation list that has yet to be viewed, and/or an application feature determined via machine learning. In some embodiments, the disclosed systems dynamically update a graphical user interface of a client device in real time as the user utilizes the client device to access and navigate the software application(s) to display these recommendations.