公开(公告)号：US20240028662A1

公开(公告)日：2024-01-25

申请号：US17970353

申请日：2022-10-20

Applicant: GOOGLE LLC

Inventor： Keun Soo Yim ,  Bogdan Caprita

IPC: G06F16/957 ,  G06Q30/06

CPC classification number: G06F16/9577 ,  G06Q30/0631

Abstract: Implementations relate to triggering suggestion(s) for a document that is at least partially displayed by a content access application at a user interface of a client computing device. The suggestions(s) can be triggered when one or more triggering conditions that provide when to trigger the suggestion(s) are satisfied. The one or more triggering conditions can include, for example, a coordinate condition, a DOM node condition, and/or a temporal condition.

公开(公告)号：US11630763B2

公开(公告)日：2023-04-18

申请号：US17457644

申请日：2021-12-03

Applicant: Google LLC

Inventor： Keun Soo Yim

IPC: G06F11/36 ,  G06F8/65

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for testing open source software are disclosed. In one aspect, a method includes the actions of receiving, from a user device and by a presubmit check server system that is configured to perform presubmit checks on system software code updates, a system software code update and a request to perform a presubmit check on the system software code update. The actions further include requesting, from a system software code server system that is configured to store system software code, presubmit check code. The actions further include receiving, from the system software code server system, a presubmit check code module. The actions further include executing the presubmit check code module against the system software code update. The actions further include providing a report that indicates results of the presubmit check code module execution against the software code update.

公开(公告)号：US20220147775A1

公开(公告)日：2022-05-12

申请号：US17252218

申请日：2020-05-29

Applicant: Google LLC

Inventor： Keun Soo Yim

IPC: G06K9/62 ,  H04L51/046 ,  H04L51/02 ,  G06N20/20

Abstract: Implementations set forth herein relate to selectively relying on additional suggestion model(s) when generating selectable suggestions, while also maintaining access to a default suggestion model. The selectable suggestions can be generated using one or more additional multi-domain machine learning (ML) models, which can be optionally available to the client application, regardless of whether a default suggestion model remains useful for generating suitable suggestions. In some implementations, as the client application employs various additional multi-domain ML models, a particular model can be identified as improving suggestions for the client application, at least based on user feedback and/or other data. The particular model can then be selected to replace and/or supplement the default suggestion model, in order to provide more accurate suggestions that, when selected, initialize actions that can preserve time and computational resources.

公开(公告)号：US20220129631A1

公开(公告)日：2022-04-28

申请号：US17082580

申请日：2020-10-28

Applicant: Google LLC

Inventor： Keun Soo Yim ,  Kyung Yul Lim ,  Umesh Patil

IPC: G06F40/295 ,  G06F40/205

Abstract: Implementations are described herein for recommending actions based on entity or entity type. In various implementations, a partial free-form natural language input may be received from a user at an input component of a computing device. The partial free-form natural language input may identify an entity without identifying a responsive action and may be directed by the user to an automated assistant that operates at least in part on the computing device. The partial free-form natural language input may be analyzed to identify the entity. Based on the identified entity, a plurality or superset of candidate responsive actions may be identified, filtered, and/or ranked based on one or more signals. The automated assistant may then provide output that recommends one or more of the candidate responsive actions based on the ranking and/or filtering.

公开(公告)号：US20220091972A1

公开(公告)日：2022-03-24

申请号：US17457644

申请日：2021-12-03

Applicant: Google LLC

Inventor： Keun Soo Yim

IPC: G06F11/36 ,  G06F8/65

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for testing open source software are disclosed. In one aspect, a method includes the actions of receiving, from a user device and by a presubmit check server system that is configured to perform presubmit checks on system software code updates, a system software code update and a request to perform a presubmit check on the system software code update. The actions further include requesting, from a system software code server system that is configured to store system software code, presubmit check code. The actions further include receiving, from the system software code server system, a presubmit check code module. The actions further include executing the presubmit check code module against the system software code update. The actions further include providing a report that indicates results of the presubmit check code module execution against the software code update.

公开(公告)号：US20190251216A1

公开(公告)日：2019-08-15

申请号：US16394069

申请日：2019-04-25

Applicant: Google LLC

Inventor： Keun Soo Yim ,  Iliyan Malchev

IPC: G06F17/50 ,  G06F9/451 ,  G06F9/455

Abstract: Methods and apparatus are described herein emulating, by one or more servers on behalf of a mobile computing device, a cloud-based virtual machine. The cloud-based virtual machine may include a virtualized hardware component that provides, as virtual hardware input for a software application executing on the cloud-based virtual machine, either “genuine” virtual hardware input or “simulated” virtual hardware input. Genuine virtual hardware input may be based on an actual hardware signal received from a hardware component of the mobile computing device that corresponds to the virtualized hardware component. Simulated virtual hardware input may be generated independently of any hardware signal associated with the hardware component. Output of the software application may be interactively streamed to the mobile computing device.

公开(公告)号：US12242528B2

公开(公告)日：2025-03-04

申请号：US17946806

申请日：2022-09-16

Applicant: GOOGLE LLC

Inventor： Keun Soo Yim

IPC: G06F16/40 ,  G06F16/435 ,  G06F16/45

Abstract: Implementations relate to processing media content, and/or associated metadata, to classify the media content into a first category, of a plurality of predefined categories. Versions of those implementations further relate to extracting target content from the media content; generating, based on the extracted target content, an action that corresponds to an application; and generating, based on the generated action, a selectable suggestion including a textual portion that describes the action. Some of those versions further relate to causing the selectable suggestion to be displayed at a display of a client device, along with rendering of the media content. The selectable suggestion, when selected, causes the application to perform the action. The target content can be extracted based on the first category and can be extracted based on the first category in response to the media content being classified into the first category.

公开(公告)号：US20240419677A1

公开(公告)日：2024-12-19

申请号：US18335705

申请日：2023-06-15

Applicant: GOOGLE LLC

Inventor： Keun Soo Yim ,  Adam Coimbra

IPC: G06F16/248 ,  G06F16/2453 ,  G06F16/2455

Abstract: Implementations include receiving search-based content donated by a first application installed at a client device, and processing the search-based content to generate a first entry in a central on-device repository that locally stores content donated by different applications installed at the client device. Implementations further include receiving, via a unified interface that is independent of the first and second applications, a search query from the user and, in response to receiving the search query via the unified interface, searching the central on-device repository to determine whether any entry in the central on-device repository is responsive to the search query. If it is determined that the first entry is responsive to the search query, an interface element is generated based on the first entry, and the generated interface element is rendered at the unified interface, for potential selection by the user.

公开(公告)号：US12147767B2

公开(公告)日：2024-11-19

申请号：US18144707

申请日：2023-05-08

Applicant: GOOGLE LLC

Inventor： Keun Soo Yim ,  Kyung Yul Lim ,  Umesh Patil

IPC: G06F40/295 ,  G06F40/205 ,  G06F40/279 ,  G10L15/19

Abstract: Implementations are described herein for recommending actions based on entity or entity type. In various implementations, a partial free-form natural language input may be received from a user at an input component of a computing device. The partial free-form natural language input may identify an entity without identifying a responsive action and may be directed by the user to an automated assistant that operates at least in part on the computing device. The partial free-form natural language input may be analyzed to identify the entity. Based on the identified entity, a plurality or superset of candidate responsive actions may be identified, filtered, and/or ranked based on one or more signals. The automated assistant may then provide output that recommends one or more of the candidate responsive actions based on the ranking and/or filtering.

公开(公告)号：US12063191B2

公开(公告)日：2024-08-13

申请号：US18241690

申请日：2023-09-01

Applicant: GOOGLE LLC

Inventor： Keun Soo Yim

IPC: H04L51/046 ,  G06F9/455 ,  H04L51/02

CPC classification number: H04L51/046 ,  G06F9/45558 ,  H04L51/02 ,  G06F2009/45587

Abstract: Implementations set forth herein relate to an automated assistant that allows third party applications to inject dependencies to leverage automated assistant functions. Furthermore, enabling such dependency injections can allow third party applications to preserve privacy of any application content that is used during execution of automated assistant functions. In some implementations, a third party application can initialize a function with an assistant dependency using parameters that are tagged as private. Initializing a function in such as a way can allow private content communicated between the third party application and the automated assistant to be abstracted for security purposes. The abstracted content can thereafter be communicated to a remote server—such as a server hosting an extensively trained machine learning model. Intelligent output provided by the server can then be incorporated into one or more processes of the third party application without comprising security.