72 results about "Context recognition" patented technology

The invention relates to the technical field of code security analysis, and discloses a control flow analysis and retrieval enhancement-based large model code security review method, which comprises the following steps of: analyzing an incremental code to generate an abstract syntax tree and data flow analysis information; retrieving local knowledge base association business rules and historical vulnerabilities based on grammatical features, and generating a context enhancement prompt; calling a large language model to jointly analyze codes and contexts, identifying vulnerabilities and outputting a structured report; and combining with a historical false alarm data optimization result and then integrating to a development assembly line. Multi-source information is fused through an RAG technology to enhance semantic understanding, and control flow node tracking and cross-version semantic association are combined, so that the problems of a traditional tool business logic vulnerability detection blind area, incremental code analysis failure and high false alarm rate are solved, synchronous improvement of security examination accuracy and efficiency is realized, and the method is adaptive to an agile development scene.

The invention discloses a law shield AI intelligent case handling all-in-one machine system based on a large language model, and relates to the technical field of law artificial intelligence and judicial informatization, the system comprises an integrated terminal device, a case semantic modeling module, a class case knowledge engine, a risk prediction module, a large language model service interface and an intelligent document generation module; the system constructs a case semantic graph through multi-modal information fusion and a graph neural network, performs legal rule path matching and similarity reasoning based on a class case database, outputs structured legal suggestions and standard legal instruments in combination with user context recognition and large language model multi-round generation capability, and realizes dynamic updating of the semantic graph. The method improves the automation, structuring and interpretability of case processing, and is suitable for intelligent case handling scenes such as legal assistance, litigation assistance and judicial mediation.

Collaborative enhanced sensing systems and techniques are described. A system obtains sensor data of an environment from one or more sensors. The sensor data includes different representations of one or more portions of the environment from multiple perspectives. The system identifies a subset of the different representations of the one or more portions of the environment based on context corresponding to a vehicle in the environment. The context can include, for example, a position, a direction of travel, a speed, and / or a planned movement of the vehicle. The system causes an enhanced representation of the environment for the vehicle to be generated at least in part based on consolidating and / or fusing together the subset of the different representations. The system can cause an indication of the enhanced representation of the environment to be output at the vehicle.

The invention relates to the field of aviation voice signal processing, and discloses a voice recognition compensation pilot earphone hearing protection method and system, and the method comprises the following steps: collecting multi-modal data, and separating a sound source through tensor decomposition; inferring a pilot state by using a dynamic network; performing context recognition and semantic evaluation on the attention target voice; and finally, dynamically modulating the sound field based on deep reinforcement learning, enhancing the voice in a personalized manner, and outputting after noise suppression. The system comprises a multi-mode perception data acquisition module, a sound source decoupling module, a pilot state inference module, a voice processing and semantic evaluation module and a sound field modulation and output module. According to the invention, high-fidelity speech extraction is realized through multi-modal perception and tensor decomposition; evaluating priority key information in combination with attention and semantics; and deep reinforcement learning and model prediction control are adopted to dynamically optimize the sound field, so that the voice recognition accuracy and the pilot information acquisition efficiency are improved.

To solve the problem that an existing neuro-symbolic system is limited to processing of single modality, has a static reflection mechanism, lacks knowledge-based extension capability and a knowledge transfer function, and does not have a feedback mechanism between a reflection process and an output generation process.SOLUTION: A neuro-symbolic artificial intelligence system comprises a multimodal encoder, a context recognition network body, an output generation layer, a hierarchical reflection module, an extensible knowledge base, a feedback loop integrator, and a meta-learning controller. The multimodal encoder transforms inputs from different modalities to unified representations, and the context recognition network body generates embeddings considering a task-specific context. The hierarchical reflection module generates a reflection vector, and the feedback loop integrator identifies errors on the basis of the reflection vector, and the extensible knowledge base is used to generate correction candidates.SELECTED DRAWING: None

The invention discloses a bill recognition method and system based on artificial intelligence image enhancement, and relates to the field of image recognition. The method comprises the following steps: S1, extracting multi-dimensional quality features based on an original image of a bill and calculating a scene consistency factor; s2, adjusting a global enhancement weight according to a scene consistency factor, adjusting a local gain in combination with a detail fidelity factor, and performing adaptive enhancement on the original image to generate an enhanced image; s3, establishing an optical flow field model to analyze geometric deformation of the enhanced image, and performing adaptive correction in combination with local deformation rigidity to generate a corrected image; and S4, analyzing gradient features and character confidence of the corrected image, extracting a candidate character region, and performing context recognition by adopting a sequence model to obtain a text field set. Scene complexity is quantified through multi-dimensional quality features, and detail fidelity self-adaptive enhancement and optical flow deformation correction of high-frequency character distinguishing are combined, so that bill character definition and recognition accuracy are remarkably improved.

The invention discloses a multi-protocol adaptive Internet of Things device communication management method and system, and relates to the technical field of Internet of Things device communication management, and the method comprises the steps: capturing an original message sent by a source device through a communication management node disposed at an edge side when an Internet of Things device initiates a communication request, obtaining a source device identifier, a target address and a transport layer protocol type of the original message; identifying a used application layer protocol according to the structural features and the communication context of the original message, extracting an operation intention contained in the original message, and generating a standardized semantic feature vector; on the basis of the difference degree between the standardized semantic feature vector and semantic feature vectors of other protocols, initial compatibility scores among the protocols are determined, and a communication topological graph is constructed in combination with real-time delay and node resource states of network links; and continuously recording communication execution results of different protocol pairs on each node, and generating a dynamic memory factor according to the change trend of the execution results.

The invention provides a chat question-answering method and device based on knowledge precipitation, equipment and a storage medium, relates to the technical field of data processing, in particular to the fields of artificial intelligence, domain knowledge modeling and the like, and can be applied to application scenes such as chat conversation intelligent question-answering and the like. The specific implementation scheme is as follows: in response to a current message event in a chat dialogue, determining context information of the current dialogue; performing intention recognition based on the context information to obtain an intention recognition result; retrieving related domain knowledge from a knowledge base based on the intention recognition result; using the retrieved domain knowledge and context information to generate candidate answers; and carrying out quality scoring on the candidate answers, screening the answers with scores reaching a preset threshold value as target answers, and sending the target answers to the chat conversation. According to the scheme, the context can be constructed in the chat conversation, the intention can be recognized, the precipitated knowledge can be retrieved, and the high-quality answer can be generated, so that real-time reliable reply is provided, efficiency and accuracy are improved, and knowledge reuse and dynamic update are promoted.

The present invention discloses a method and system for correcting interviewer evaluation bias based on real-time feedback, which specifically relates to the field of human resource management technology. The method and system are used to solve the problems in existing recruitment systems where evaluation standards are out of touch with industry characteristics due to standardized semantic parsing, and interviewers' implicit evaluation bias is difficult to correct dynamically. The method dynamically parses fuzzy terms in job requirements through an industry knowledge base, generates industry weights and terminology thresholds, collects interview interaction texts in real time, and analyzes the correlation between candidates and terminology thresholds. The method combines interviewer question context recognition and deviation calculation to mark terminology deviation signals and repeated question intention deviations, and finally dynamically adjusts the scoring weights according to industry correction rules. The semantic parsing and real-time feedback linkage mechanism adapted to industry characteristics achieves the alignment of evaluation standards with the actual job requirements, effectively eliminates evaluation bias caused by misunderstanding of terminology, and improves the objectivity and accuracy of talent selection.

An information processing device (1) comprises a reception unit (31), a determination unit (34), an identification unit (35), and a provisioning unit (36). The reception unit (31) receives a search query from a user belonging to an organization. The determination unit (34) determines a user context on the basis of user information and the search query received by the reception unit (31). The identification unit (35) identifies, as a target user, another user who belongs to the organization and who has a past or current context that is similar to or matches the user context determined by the determination unit (34). The provisioning unit (36) provides information pertaining to the target user identified by the identification unit (35).

The invention relates to the technical field of data transmission, and particularly provides a streaming Token double-path transmission method, system and device and a storage medium, and the method comprises the steps: responding to a streaming request, completing the initialization of a system and a session, building a bypass channel from a model to a client, and creating a session context in a control flow engine; identifying the type of each Token generated by the model, and shunting according to the type: data Token routing to a bypass channel and control Token routing to a control flow path processed by a control flow engine; data bypass transmission and control flow service processing are executed in parallel, and the states of the data bypass transmission and the control flow service processing are ensured to be consistent through a state synchronization mechanism; and the dual-path operation state is continuously monitored, and dynamic path adjustment or abnormity recovery is carried out when abnormity is detected. According to the method, the data flow and the control flow are decoupled, so that the transmission delay of the streaming Token is remarkably reduced while the state consistency is ensured.

The application discloses a tourist sentiment analysis method based on a large language model, and belongs to the technical field of intelligent scenic spot management, and solves the problems of poor real-time performance, low Chinese context recognition accuracy, insufficient multi-modal fusion, lack of multi-region sentiment linkage prediction and closed-loop management capability in the prior art. The core steps of the method include: S1 data acquisition and preprocessing, S2 basic sentiment calculation, S3 Chinese context enhancement correction, S4 final sentiment value fusion calculation, S5 regional sentiment index construction and early warning, S6 closed-loop feedback regulation, and the S7 multi-region sentiment coupling prediction and pre-intervention step is additionally added. The application supports text and voice multi-modal data acquisition, designs a special sentiment correction mechanism for Chinese context, can realize real-time analysis of tourist sentiment, negative emotion early warning and pre-intervention, and forms an operation optimization closed loop, and provides accurate decision basis for fine management of intelligent scenic spots.

Systems and methods for transferring link context to a web browser. An example method includes receiving, by a web browser, a web address from a desktop application based on a selection of a link in document displayed in the desktop application; receiving, by a web browser from the application, link context for the selected link, the link context including an identification of the desktop application and an identification of the document; loading a web page corresponding to the received web address; based on the link context, identifying a browser-based application corresponding to the desktop application; launching the browser-based application within the web browser; transmitting the link context to the browser-based application; and displaying at least a portion of the document within the web browser.

The application relates to the field of data processing, and provides a multi-process DMA access method and device based on device end context recognition and a chip. The method comprises the following steps: when initiating a DMA operation, a target VF generates a DMA request containing a local virtual address of the target VF; a VFID corresponding to the target VF is extracted from the DMA request, a virtual function address conversion table in a terminal device is inquired according to the VFID, and an address mapping table is acquired; the local virtual address of the target VF is converted into a corresponding DVA through the address mapping table; a standard PCIe TLP is generated based on the converted DVA; and the TLP is sent to a host, so that an input / output memory management unit or an address conversion service on the host side converts the DVA into a host physical address HPA, and the DMA operation is completed. Through the front movement of the multi-process address conversion from the host side to the terminal device side, a more efficient DMA access path is realized without relying on a PASID.

A system can comprise a memory that stores computer executable components, and a processor that executes the computer executable components stored in the memory. The computer executable components can comprise a correlation component that, based on a first context defining a first spare resource instance to be utilized in a networked system, identifies a second spare resource instance, and an evaluation component that generates an availability score defining prediction of availability of the first spare resource instance based on a second context defining the second spare resource instance, wherein the evaluation component further deploys the first spare resource instance, based on the availability score, in the networked system.

A context-aware Al system for editing interface elements of a site includes a visual interface that receives user interaction and presents visual output; a conversational interface that receives natural language instructions and presents natural language messages; a context recognition module that identifies elements, computes a respective score for each element based on semantic similarity between the instructions and element's metadata and select elements having scores satisfying a criterion; a context management module that maintains an active editing context identifying elements and data associated with them, and updates the active editing context in response to an operation received via the visual interface or via the conversational interface; an interface assistant that generates editing operations based on the natural language instructions; a visual reaction module that applies the editing operations on the visual interface; and a conversational reaction module for displaying natural language messages on the conversational interface.

The invention provides a production and warehouse management business-oriented domain-driven design method. The method comprises the following steps of S1, constructing a domain design standard to divide a domain and a sub-domain; and S2, carrying out aggregation division through a domain design standard. S3, realizing limit context identification through a domain design standard, dividing a service boundary based on aggregation information, and identifying a limit context; a micro service is split into an aggregation service layer and an atomic service layer, and a domain design standard is used as a division basis of the aggregation service and the atomic service. And S4, using a four-layer code architecture to develop the atomic service. And S5, realizing a cross-domain business process through micro-service arrangement. The method has the beneficial effects that by introducing an aggregation + atomic service architecture, the high-cohesion and low-coupling service design is realized, so that the system can more flexibly respond to the change of service requirements. The unified domain model is constructed by emphasizing the domain driving design, so that the data consistency among the business modules is ensured, and the integration difficulty is reduced.

A method includes receiving, at a search toolbar, a search query from a machine in a network. The machine has an associated machine profile for participating in the network as an entity. The machine profile includes a machine identifier and machine metadata. A query type is determined from the search query. A search context for the machine is determined using a semantic graph of the network. From a set of services for the network, one or more relevant services to respond to the search query are identified based on the query type and the search context. The search query is applied to the one or more relevant services to obtain a set of responses. A set of relevant results for the search query is determined from the set of responses. The set of relevant results is transmitted to the machine.

The application discloses a kind of big language model-based legal shield AI intelligent case handling integrated machine system, it is related to legal artificial intelligence and judicial informatization technical field, the system includes integrated terminal equipment, case semantic modeling module, case knowledge engine, risk prediction module, big language model service interface and intelligent document generation module;The system constructs case semantic graph by multi-modal information fusion and graph neural network, carries out legal rule path matching and similarity reasoning based on case database, combines user context recognition and big language model multi-round generation capacity, outputs structured legal opinion and standard legal document, and realizes semantic graph dynamic update;The application improves the automation, structure and interpretability of case processing, and is suitable for legal aid, litigation assistance, judicial mediation and other intelligent case handling scenarios.

A method for enhancing image quality using an electronic device is provided. The method includes receiving, by the electronic device, an image frame from a network, monitoring, by the electronic device, a network parameter of the network, determining, by the electronic device, a context of the electronic device, identifying, by the electronic device, a visual degradation in the image frame based on the monitored network parameter and the context of the electronic device, and modifying, by the electronic device, a visual quality factor of the image frame based on the visual degradation in the image frame for enhancing the image quality.

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for receiving a request to identify a set of one or more relevant digital credentials from a plurality of digital credentials associated with a digital credential application on a mobile device; identifying a context for the request; identifying, as candidate digital credentials, a subset of the digital credentials associated with the digital credential application; processing an input comprising (i) the context for the request and (ii) data characterizing each of the candidate digital credentials using a neural network to generate an output that defines a relevance ranking of the candidate digital credentials given the context for the request; selecting, as the set of one or more relevant digital credentials, one or more of the candidate digital credentials using the output; and presenting, on the mobile device, data representing the set of one or more relevant digital credentials.

The present disclosure relates to a method and device for predicting object motion based on context recognition. Additionally, the present disclosure relates to a method for establishing a moving object path plan based on pedestrian motion prediction in a moving object capable of autonomous driving, using the method for predicting object motion based on context recognition. The method for predicting object motion based on context recognition, according to the present disclosure, includes generating a semantic map for context information associated with an object, generating a motion flow map that includes the motion flow for each object, generating a motion-semantic map based on the semantic and motion flow maps, and performing motion prediction of at least one object based on the motion-semantic map.

A governance enforcement architecture conditions completion of commit-capable state transitions in heterogeneous operational environments. A context intake component acquires attributes associated with a pending durable state mutation, and a rule selection engine identifies an applicable rule set based on jurisdictional, organizational, contractual, regulatory, or domain-specific context. A governance evaluation engine generates an authorization outcome prior to persistence. An execution-path control component positioned in-line with a commit pathway selectively permits, suspends, or denies completion of the state transition in accordance with the authorization outcome. A dissent state is generated when evaluation produces non-convergent results. A tamper-evident governance record stores lineage data including rule version, evaluation context, and resulting governance state, enabling deterministic replay across distributed environments.

The invention relates to the technical field of sentiment analysis, in particular to an AI-based sentiment analysis platform, which comprises a phrase structure segmentation module, a tag density judgment module, a sentiment trend classification module, a polarity turning recognition module and a convolutional image focusing module. According to the method, the phrase number and the word number before and after each punctuation are extracted by recognizing the positions and pause distribution of the punctuations in the paragraphs, and the phrase boundary is determined according to the phrase distribution fluctuation degree, so that phrase division is more fit with a natural semantic structure, and the accuracy of sentiment analysis in context recognition is remarkably improved; a shielding layer is generated according to a mutation region, a high-signal-noise feature mapping region is reserved, and the structural focusing degree of a convolution result is optimized, so that an emotion recognition result is more discriminative, and the precision and stability of emotion recognition are remarkably improved in multiple aspects of context association, polarity mutation recognition and feature extraction; and the adaptive capacity and the processing efficiency of sentiment analysis in a complex context are enhanced.

A method, computer system, and computer program product are provided for processing wage payments to an employee according to an employee-specified pay schedule. A computer system receives a payroll event for an employee. In response to receiving the payroll event, the computer system interprets a first structured data object for processing payroll. In interpreting the first structured data object, the computer system identifies an employee-specified pay schedule according to an employee context interpreted from the first structured data object. In interpreting the first structured data object, the computer system determines that a wage payment should be made to the employee according to the employee-specified pay schedule. Responsive to determining that the wage payment should be made, the computer system transmits an order for the wage payment to the employee to a specified wage payment proxy server via a network using a specified communication channel to pay the employee.

Disclosed are methods, systems, and computer-readable medium to perform operations including: receiving coded data comprising a plurality of data elements, each data element comprising a coded message; determining, for a coded message and based on a semantic model, a semantic distortion value, the semantic model comprising one or more classifiers configured to identify a desired meaning of a given coded message based on a context of the given coded message; determining a difference between the semantic distortion value and a baseline semantic distortion value; and generating, when the difference exceeds a threshold value, a security message indicating a potential security issue.

The invention relates to the technical field of voice recognition, in particular to an intelligent telephone traffic system which comprises a signal verification module, a voiceprint separation module, a content transfer module, an intention chain construction module and a priority judgment module. According to the method, in the voice input process, stability verification is achieved through comparison of the breathing flow velocity curve and the fundamental frequency period, it is guaranteed that recognition signals are consistent, breathing fluctuation deviation is reduced, acoustic features are corrected through alignment of the oral formant and the voiceprint template, and the voice is closer to real voice; multi-source scene analysis formant position and bandwidth change improves sound channel difference to avoid feature aliasing of speakers, phoneme boundaries are subjected to difference value and sequence rearrangement to realize stable time sequence matching to ensure consistent transcription, intention processing is combined with verb object time chain arrangement to generate distinguishable priorities in conflict judgment to ensure multi-intention semantic coherence and accuracy, and multi-intention semantic coherence is realized. Input stable signals are integrally formed to distinguish time sequence optimization intention sequencing continuous links, and the complex context recognition precision and logic rationality are improved.

A user registers for an account with an account management system, configures account settings to permit the account management system to receive user computing device data from a user computing device associated with the user, and logs into the account via the user computing device. The account management system receives a user voice purchase command and determines a purchase command context based on the received user computing device data. The account management system identifies a product that the user desires to purchase based on the purchase command context and directs the user computing device web browser to a merchant website to set up a transaction for the identified product.

The invention relates to a user behavior analysis method and device based on a small sample, and the method comprises the steps: collecting user operation data, and processing the user operation data to obtain target data; the target data comprises user context information; configuring a user behavior context recognition rule, and constructing a user behavior context according to the user behavior context recognition rule and the target data; training a user behavior recognition and intention inference model through the user behavior context; and utilizing the trained user behavior recognition and intention inference model to recognize to-be-detected user behavior data, and generating a corresponding user behavior abnormal risk description. A user behavior context construction technology based on a small sample is utilized to provide a user abnormal behavior recognition basis, a user behavior abnormal risk is automatically recognized and generated through a user behavior recognition and intention inference model, the user behavior recognition and intention inference model carries out self-evolution and self-learning along with gradual access of data, and the user behavior abnormal risk is automatically recognized and generated. And the model abnormity identification capability is continuously improved.

An identity verification system receives context signals from an authenticating computing device in response to a target user requesting access to a secure asset. The identity verification system identifies candidate locations for the operational context assigned to historical context signals labeled as being measured at a known location and compares the context signal to each historical signal to determine a location of the operational context corresponding to the received context signal. The identity verification system determines a match probability for the target user based on a risk score assigned to the location of the operational received context signal and grants the requesting target user access to the secured asset in response to determining that the match probability is greater than the operational security threshold.