16 results about "Context type" patented technology

The invention discloses a document proofreading system and method based on artificial intelligence, and relates to the technical field of natural language processing, and the method comprises the steps: analyzing a document, dividing semantic units, and obtaining a document with a context label based on context type library labeling; performing initial error detection by using the corresponding rule set, and comparing the format of the document and the text quality characteristics with a standard sample vector space to obtain an initial error set; constructing a defect conduction chain network, and locating root cause error nodes causing a plurality of secondary errors by tracing the defect conduction chain network; generating an intelligent proofreading report; receiving a new-version document revised by the user, comparing the new-version document with the original-version document, positioning a change area, and analyzing a quality difference of the change area on a related quality dimension; based on the quality difference, an incremental proofreading report is output, and the incremental proofreading report comprises newly introduced errors and unsolved root cause errors.

The invention discloses a smart home control method based on voice recognition and context awareness. The method comprises the following steps: S1, collecting voice signals and environment state information; s2, performing preprocessing on the voice signal; s3, inputting the speech feature sequence into a speech recognition model based on a recurrent neural network transduction structure for recognition processing, and outputting a semantic text sequence; s4, constructing a two-stage trigger matching strategy, and if a matching result exists, determining that the request is a voice wake-up request; s5, executing situation classification, and outputting a current situation type label; and S6, according to the current situation type label, generating different instructions. According to the invention, by fusing voice recognition and environment perception, high-accuracy smart home control suitable for an aged scene is realized, and the system has timely response and personalized interaction capabilities.

The invention discloses a context information management method and device, equipment, a medium and a program product, and relates to the technical field of data processing, and the method comprises the steps that a first component command is acquired, and the first component command carries a collection range of context information; the execution of the context component is triggered based on the first component command to obtain a first vector library, the first vector library is in one-to-one correspondence with the context type of the context information, and the context component is configured to be provided with a context acquisition module, a context processing module, a context storage module and a context retrieval module; the context storage module is used for storing the processed context information based on the context type of the processed context information, the context retrieval module is used for providing a retrieval tool aiming at the first vector library, and the retrieval tool is configured to be provided for the context processing module to call or provide a first object call of a first component command. According to the method, the context information in the first vector library can be efficiently and accurately obtained.

Embodiments of the present application provide a log processing method, apparatus, device, and storage medium, which obtain operating environment information of a mobile terminal and record a log corresponding to the log level and the operating environment information; obtain context type information of the log and store the log according to a storage policy corresponding to the context type information; obtain the application scenario type of the mobile terminal and upload the log according to an upload policy corresponding to the application scenario type of the mobile terminal; and can adopt different recording strategies, storage strategies, and upload strategies for different situations to achieve a more optimal log processing strategy and improve the operability of the log of the mobile terminal.

The invention relates to an SQL (Structured Query Language) statement extraction method and device, electronic equipment and a storage medium. The method comprises the following steps: acquiring an SQL script file to be processed; a target state machine corresponding to the SQL script file is determined, the target state machine comprises a plurality of states and switching conditions among different states, the states are used for indicating context types in the SQL script file, and the switching conditions are used for indicating rules of context changes in the SQL script file; traversing each character in the SQL script file according to a plurality of states and switching conditions in the target states, so that the target state machine is switched among different states; and in the process of traversing each character in the SQL script file, extracting all executable SQL statements from the SQL script file according to the state of the target state machine. According to the method, the accuracy of SQL statement extraction is improved.

The invention provides a task allocation method and device, and the method comprises the steps: building a knowledge graph according to the task data of a to-be-allocated task and the employee data of each candidate employee, the task data comprises task skills required by the to-be-allocated task, and the employee data of the candidate employees comprises employee skills; obtaining the score of each candidate employee under each reference dimension according to the knowledge graph, wherein each reference dimension at least comprises a skill matching dimension; adjusting a preset weight corresponding to each reference dimension through a situation type sensed by a situation sensing engine to obtain a corrected weight corresponding to each reference dimension, wherein the situation type comprises at least one of an emergency task, employee absence, skill change and team cooperation conflict; according to the score of each candidate employee under each reference dimension and the correction weight corresponding to each reference dimension, obtaining a matching degree between each candidate employee and the to-be-allocated task; and the to-be-allocated tasks are allocated according to the matching degree, so that the allocation efficiency can be improved.

A system for processing and integrating contextual information across multiple time scales simultaneously analyzes immediate and historical data. The system comprises three main components working together to maintain temporal coherence. A temporal processing engine processes input data at different time scales using multiple processors, each dedicated to a specific time horizon. A context integration engine extracts and organizes contextual features from the input data, generating representations for different types of context while maintaining state information across these context types. A fusion engine combines the outputs from the temporal processors and integrates them with the context representations to generate coherent, unified outputs. The three engines operate cooperatively to ensure temporal consistency while processing context across multiple time scales. This architecture enables robust handling of complex temporal and contextual relationships, supporting applications in fields such as customer service, healthcare monitoring, and interactive systems where maintaining coherence across time scales is crucial.

Systems and methods for providing a machine learning assisted communication tool are provided. A method for using machine learning to aid communication may include: receiving inputs, via a user input device, the received inputs including: a message input indicative of a message to be communicated; and one or more contextual inputs associated with the message to be communicated, each contextual input having an associated context type; generating a prompt based at least in part on the received inputs and the associated context types of the one or more contextual inputs; and determining, using a machine learning model, one or more outputs associated with the message to be communicated based at least in part on the generated prompt, at least one output of the one or more outputs being a message output indicative of the message to be communicated based at least in part on the received inputs.

The invention discloses a task processing method and device for cloud collaborative scheduling, articulated naturality web equipment, a medium and a product. The method comprises the following steps: acquiring a situation feature of an articulated naturality web task in an articulated naturality web scene; inputting the situation feature into a situation feature extraction model to obtain a situation type output by the situation feature extraction model and a prediction confidence coefficient corresponding to the situation type; wherein the prediction confidence is a deterministic evaluation index of the situation feature extraction model for the extracted situation type; and selecting a cloud collaborative scheduling mode to process the articulated naturality web task according to the situation type and the prediction confidence coefficient.

This information processing device: acquires a video to be monitored; analyzes a video frame constituting the video to extract, for each type of context indicating attributes of objects included in the video frame constituting the video and / or the relationship between the objects, a first feature amount related to the context from the video frame; executes, on the basis of information on a topic of interest related to the video, sampling processing on the extracted first feature amount related to the context; and outputs, on the basis of the first feature amount on which the sampling processing has been executed, an answer to a request related to the video.

A method for context-based natural language processing is disclosed herein. The method comprises maintaining a plurality of dialog system rules, receiving a user request from a Dialog System Interface, receiving one or more attributes associated with the user request from the Dialog System Interface or a user device, and identifying a type of context associated with the user request based on the user request and the one or more attributes. A context label is assigned to the user request associated with the type of context. Based on the context label and the user request, a particular dialog system rule is selected from the plurality of dialog system rules. A response to the user request is generated by applying the dialog system rule to at least a part of the user request.

The invention discloses an OpenGL (Open Graphics Library) GPU (Graphics Processing Unit) simulation method supporting multi-context and off-screen rendering, which comprises the following steps of: providing a client graphic API (Application Program Interface) replacement component, intercepting API call and collecting context creation information; when a client program creates an OpenGL context, a process ID, a thread ID and a context handle are extracted, a unique context identifier is generated, and a corresponding communication channel is allocated according to a context type; the data is sent to the host machine side simulator module through a shared memory or a network communication mechanism; constructing a frame buffer object and taking the frame buffer object as a rendering output target; the main window context can multiplex texture resources generated by off-screen context rendering through a standard texture binding interface, and outputs a synthesis result to a display window; and the host machine triggers a context resource release operation. Comprehensive multi-context support, off-screen rendering compatibility and resource isolation capability are provided for an OpenGL GPU simulation system, and simulation correctness and function coverage under a complex graphic application scene are remarkably improved.

Systems and methods for securely exposing context-driven services within a web browser. An example method includes receiving manifests from hubs apps (e.g., remote services). The manifests define requested context types for the hub apps. When the web browser loads a web page, the web browser may execute context extractors to extract context from the web page. The context extractors that are executed are based on the context types requested by the hub apps. The extracted context is then sent to the corresponding hub apps without providing the hub apps direct access to the web page. For instance, the hub apps do not have access to the document object model (DOM) of the web page and the hub apps cannot inject data into the web page.

This application discloses a mouse-triggered cross-application file context processing method, system, and computer-readable storage medium, relating to the fields of human-computer interaction, operating system context capture, and artificial intelligence office processing. The client software initiates a resident context capture process, periodically detects the foreground window and determines the application type, and obtains the currently active file, webpage address, or selected file through cross-process reading or file handle enumeration based on application automation interfaces, accessibility interfaces, file manager interfaces, and desktop list controls. A unified context object is constructed and written to the cache and pushed when the object changes. In response to mouse smart button triggers, natural language instructions are obtained and the target context object is read. The structured operation intent is obtained through intent parsing and routed to the execution module according to the context type and intent type to perform file processing, webpage content processing, document content processing, content generation, document write-back, or system operations on the current operation object.

The application discloses a document proofreading system and method based on artificial intelligence, and relates to the technical field of natural language processing.The method comprises the following steps: analyzing a document, dividing semantic units, and marking based on a context type library to obtain a document with context labels; using a corresponding rule set to perform initial error detection, comparing the format and text quality characteristics of the document with a standard sample vector space to obtain an initial error set; constructing a defect propagation chain network, locating root error nodes that cause multiple secondary errors by tracing the defect propagation chain network; generating an intelligent proofreading report; receiving a new version of the document revised by a user, comparing the new version of the document with the original document, locating a change area, and analyzing the quality difference of the change area in related quality dimensions; based on the quality difference, outputting an incremental proofreading report, wherein the incremental proofreading report comprises newly introduced errors and unsolved root errors.

The application relates to the field of artificial intelligence and emotion computing technology, and particularly discloses a micro-expression recognition method and system based on context perception and multi-modal routing, which comprises the following steps: respectively performing heterogeneous feature extraction on a visual micro-motion video segment, an audio segment and transcription text of a current sentence, and an audio segment and transcription text of context data; performing cross-modal fusion and sequence compression; generating context type embedding according to a context type label; extracting context perception sentence features through a context cross-attention mechanism; obtaining visual classification confidence based on a visual micro-motion feature tensor, and comparing the visual classification confidence with a preset threshold to generate an emotion classification result. Through a layer focusing fusion network, the application realizes high-dimensional heterogeneous feature extraction and emotion inducement analysis on facial micro-deformation caused by a multi-modal stimulus context, so that accurate prediction of concealed micro-expression is realized.