23 results about "Application actions" patented technology

Indexing application actions for voice-based execution is provided. An indexer of a device receives, from an application executed by the device, an indication of an action and a deep link corresponding to the action declared by the application via an application programming interface. The indexer accesses an index stored in the memory of the device that is accessible to a plurality of applications. The indexer inputs, into a location in the index, the action and the deep link with a cryptographic token that prevents access to the deep link by unauthorized applications. A digital assistant of the device receives a voice query detected by a microphone and parses the voice query to determine the action. The digital assistant identifies in the index the deep link corresponding to the action. The digital assistant invokes, with the cryptographic token, the deep link to cause the application to perform the action.

Implementations include recognizing entities in a user query received from a client device and determining whether any of the recognized entities is a personal entity using an entity database storing personal entities donated by applications installed at the client device. Application(s) or application action(s) can be determined based on entity information of the recognized entities, and suggestions can be generated to suggest the determined application(s) (or the determined application action(s)). For an application (or application action) determined based on a recognized entity that is determined as a personal entity, a suggestion for the application (or application action) can be boosted for display to a user of the client device.

Implementations set forth herein relate to providing selectable autofill suggestions, which correspond to application actions that are at least partially fulfilled using server command data—prior to a user selecting a particular selectable autofill suggestion. Proactively fulfilling command data in this way mitigates latency between user selection of a suggestion and fulfillment of a particular action. Initially, a partial input can be processed to generate autofill suggestions, which can be communicated to a server device for further processing. The autofill suggestions can also be rendered for selection at a touch display interface, thereby allowing a user to select one of the autofill suggestions. As command fulfillment data is provided by the server, the command fulfillment data can be available to a corresponding application(s) in order that any corresponding actions can be at least partially fulfilled prior to user selection.

Various examples are directed to systems and methods for supporting an application. A training automation tool may receive process data describing an application process is to be performed by a user with the application. The training automation tool may execute a trained computerized model to generate an indication of an application test case for testing at least one feature of the application associated with the application process. The training automation tool may generate a set of application actions for performing the application process.

Implementations include recognizing entities in a user query received from a client device and determining whether any of the recognized entities is a personal entity using an entity database storing personal entities donated by applications installed at the client device. Application(s) or application action(s) can be determined based on entity information of the recognized entities, and suggestions can be generated to suggest the determined application(s) (or the determined application action(s)). For an application (or application action) determined based on a recognized entity that is determined as a personal entity, a suggestion for the application (or application action) can be boosted for display to a user of the client device.

Implementations set forth herein relate to a system that employs an automated assistant to further interactions between a user and another application, which can provide the automated assistant with permission to initialize relevant application actions simultaneous to the user interacting with the other application. Furthermore, the system can allow the automated assistant to initialize actions of different applications, despite being actively operating a particular application. Available actions can be gleaned by the automated assistant using various application-specific schemas, which can be compared with incoming requests from a user to the automated assistant. Additional data, such as context and historical interactions, can also be used to rank and identify a suitable application action to be initialized via the automated assistant.

A system and method are provided for context-aware virtual assistance and cross-application action execution based on real-time visual input. A client device captures real-time images of a real-world environment and analyzes the images to identify objects or regions of interest. Eye-tracking information is used to determine user interest in the identified objects or regions, and a user context is determined based on visual information, eye-tracking information, and a history of user interactions aggregated across multiple applications. Computer-generated visual content is presented as an overlay on the real-time images based on the determined user context, the overlay comprising a recommendation for a follow-on action associated with a second application. The response is presented via at least one of text, synthesized speech, or computer-generated visual content on a wearable display. Upon detecting user acceptance, the system causes execution of the follow-on action by the second application.

A client device associated with a user of a location-based application detects client devices associated with other users which are within proximity of the client device. This detection of other client devices may result in various application actions occurring, such as triggering a multi-user activity between users. Detection of client devices may be performed using personal area network devices of the client devices, such as Bluetooth. Proximity detection can occur when client devices are disconnected from an online system hosting the location-based application with the detection later being reported to the online system by one or both devices.

To provide a selectable GUI element when a user interacts with an application that can be controlled via an automated assistant.SOLUTION: A method includes the steps of: when an assistant operation is compatible with an application that is executed at a computing device, rendering a selectable element on a display; detecting, by an automated assistant, touch selection of the selectable element; after the touch selection, performing voice recognition of spoken utterance; and in response to the spoken utterance, causing the automates assistant to control the application on the basis of the assistant operation and a particular value of a parameter.SELECTED DRAWING: Figure 1B

An application operation method and apparatus, a configuration method and apparatus, a terminal, a server, and a storage medium. The application operation method comprises: a terminal determining a first operation instruction set on the basis of first information input by a user (301), wherein the first information represents the operation intent of the user; on the basis of a plurality of pre-configured association relationships, determining a first operation combination associated with the first operation instruction set (302), wherein each association relationship is used for associating an operation instruction with an operation combination used for executing the operation instruction, the operation combination represents an operation sequence consisting of a plurality of elements of different categories, the categories of the elements comprise an application function and / or an application action and / or application content, and the first operation combination is used for executing the operation instructions in the first operation instruction set; configuring operation parameters for all or some elements in the first operation combination on the basis of the first information (303); and executing the first operation combination configured with the operation parameters (304).

The embodiment of the invention discloses an application identification method and a related device, and the method comprises the steps: obtaining parameter information, the parameter information is used for creating a connection, and the connection is used for bearing a data stream; and performing identification processing on the parameter information, and determining an application type corresponding to the data stream. According to the application type corresponding to the data stream, the data stream is recognized to determine one or more recognition results, and each recognition result indicates at least one application action corresponding to the data stream. And through two-stage identification, the efficiency and the identification precision of application identification are improved.

According to at least one implementation, a method includes identifying a command from a user of a device. In response to the command, the method further includes identifying an image associated with a gaze of the user and identifying an action based on an application of a language model to the command and the image, the application of the language model including an identification of an object for the command in the image.

A computer-implemented method for automating cross-application actions includes providing, to a user computing system, a user interface of an object within a first application. The method further includes receiving, via the user interface, an input from the user computing system, where the input is associated with a request to take an action with a second application, and where the action uses content associated with the object of the first application. Additionally, the method includes performing the action with the second application based at least in part on receiving the input.

In one aspect, for each open application, obtain a current application state and an application content; determine one or more relationships between the application state and the application content; use the one or more relationships between the application state and the application content to determine a user intent; for a currently used application, determine a match between an application function and the user intent; and suggest an automatic action for the application function based on the match between an application function and the user intent.

The application relates to a cross-application advertisement behavior information application tracking method, device and equipment, which comprises the following steps: in response to the action of backing up cross-application advertisement behavior information, sending application action information indicating the reporting of application advertisement behavior information to a second application program; constructing a feature vector according to the application action information and the advertisement behavior information; generating an application tracking fingerprint corresponding to the second application program according to the feature vector, adding the application tracking fingerprint to the advertisement behavior information and saving the application tracking fingerprint; backing up the advertisement behavior information with the added application tracking fingerprint to the second application program through pixel code of the second application program, and in response to the application action on the advertisement behavior information, obtaining the application action information corresponding to the application action through the application tracking fingerprint; generating a matching fingerprint for the application action according to the application action information, matching the matching fingerprint with the application tracking fingerprint, and obtaining the application tracking result of the application for the advertisement behavior information.

The embodiment of the invention provides an intelligent identification method and device for a force application action based on AI and multiple sensors, and relates to the technical field of computers. The method comprises the steps that multi-dimensional data corresponding to array nodes contained in a contact surface array in target massage operation are obtained, the array nodes are arranged at equal intervals, and each array node except boundary nodes in the array nodes at least comprises a preset number of neighbor nodes; performing feature extraction on the respective multi-dimensional data of each array node to obtain the respective initial feature vector of each array node, and according to the spatial adjacency relation of each array node, updating each obtained initial feature vector to obtain an embedded vector of the target massage operation; and fusing the time sequence information and the space information of the embedded vector to obtain a target modeling vector, and determining a force application action recognition result of the target massage operation based on the target modeling vector. In this way, the force application action can be accurately quantified and recognized through the multi-dimensional data.

Embodiments of the present application disclose an application identification method and a related apparatus. The method comprises: acquiring parameter information, the parameter information being used for creating a connection, and said connection being used for carrying a data stream; performing identification on the parameter information, and determining an application type corresponding to the data stream; and, on the basis of the application type corresponding to the data stream, performing identification on the data stream to determine one or more identification results, each identification result indicating at least one application action corresponding to the data stream. By means of two-stage identification, the efficiency and identification precision of application identification are improved.

Implementations set forth herein relate to a system that employs an automated assistant to further interactions between a user and another application, which can provide the automated assistant with permission to initialize relevant application actions simultaneous to the user interacting with the other application. Furthermore, the system can allow the automated assistant to initialize actions of different applications, despite being actively operating a particular application. Available actions can be gleaned by the automated assistant using various application-specific schemas, which can be compared with incoming requests from a user to the automated assistant. Additional data, such as context and historical interactions, can also be used to rank and identify a suitable application action to be initialized via the automated assistant.

There is provided a system for authentication of a subscriber for accessing a service hosted by an application server using a mobile device, comprising: a processor of an authentication server executing a code for: obtaining an authentication request for authenticating a unique identifier of circuitry installed in a mobile device from an application server hosting a service, sending a message including the unique identifier of circuitry of the mobile device to a mobile network server, receiving a unique identifier of hardware of the mobile device from the mobile network server, wherein the unique identifier of hardware of the mobile device comprises a self-generated unique identifier generated based on unique data that is hard-wired into the mobile device, validating that the unique identifier of hardware of the mobile device corresponds to the unique identifier of circuitry of the mobile device, and sending an outcome of the validation to the application server.

Systems and methods identify, via a peer-to-peer digital network, occurrence of a triggering event, the triggering event initiating at least one notification transmission. Based on the identifying, the at least one notification is transmitted, via a telecommunications network, to user device(s), the notification including a deep link uniform resource locator (URL) of an entity webpage of an entity, the entity being different from the peer-to-peer digital network. It is determined that the deep link URL has been selected via a user device of the user device(s) and display, via a user interface of the user device, of the entity is initiated, where the entity webpage includes input field(s) to initiate action(s) via the peer-to-peer digital network.

To provide a selectable GUI element when a user interacts with an application that can be controlled via an automated assistant.SOLUTION: A method includes the steps of: when an assistant operation is compatible with an application that is executed at a computing device, rendering a selectable element on a display; detecting, by an automated assistant, touch selection of the selectable element; after the touch selection, performing voice recognition of spoken utterance; and in response to the spoken utterance, causing the automates assistant to control the application on the basis of the assistant operation and a particular value of a parameter.SELECTED DRAWING: Figure 1B

A computer-implemented system and method transform text within documents using a generative process that enables automated application of action definitions across multiple document elements while maintaining user control. For each element in a document, the system identifies an action definition and applies it to generate output by providing prompts to a large language model. The system manifests generated outputs to users for review and, upon approval, revises corresponding elements based on approved outputs. This enables efficient processing of multiple document elements while preserving precise user control over content updates. The system supports various levels of user involvement, from fully automated processing to interactive refinement, allowing users to review outputs before document updates while maintaining coherence and quality. The implementation integrates sophisticated text transformations seamlessly into document creation workflows through systematic identification and application of action definitions, combining the efficiency of automated generation with manual oversight control.