1496 results about "Interaction interface" patented technology

A method for facilitating conversational interaction with users to help the users includes transmitting a conversational interaction interface for conversationally interacting with a user to a user device, receiving a request of the user through the conversational interaction interface from the user device, identifying an information based on the request, generating an input comprising the request and the information for a machine learning model based on the request and the information, processing the input using the machine learning model, generating a response for the request based on the processing of the input, transmitting the response through the conversational interaction interface for conversationally interacting with the user to the user device, and storing the machine learning model, the request, and the response.

The invention provides a network security and data security comprehensive analysis method and system based on a large model, and the method comprises the steps: collecting multi-source heterogeneous security data of a network communication link, a data storage node and an application interaction interface, carrying out the risk behavior atomization association processing, and constructing a dynamic risk association hypergraph; based on a preset security domain knowledge graph, calling the large model to execute multiple rounds of risk attribution reasoning, performing attack chain fragment matching and evidence chain completion on a behavior hyperedge set in the dynamic risk association hypergraph, and generating a risk attribution reasoning chain; and constructing a risk evolution probability model according to the risk attribution reasoning chain and the time sequence constraint set of the dynamic risk association hypergraph, and calculating a short-term diffusion probability and a long-term evolution trend vector of each association risk path based on the risk evolution probability model to obtain a risk evolution path prediction result. The pertinence and the dynamic adaptability of protection measures can be improved, and the problem that a static protection strategy is difficult to deal with the hysteresis quality of dynamic risk changes is solved.

The invention discloses a bridge management and maintenance decision-making system and method based on multi-agent collaborative optimization, and the system comprises a monitoring agent which is deployed in a cloud server and is used for obtaining abnormal data in a bridge structure and environment data; the diagnosis agent is used for evaluating the health state of the bridge by utilizing a built-in knowledge base, a built-in machine learning model and a built-in physical model based on the abnormal data; the decision-making agent is used for generating a plurality of candidate maintenance schemes based on an evaluation result, and screening out an optimal scheme by integrating the comprehensive utility of each scheme and the resource matching degree score of the resource scheduling agent on each scheme; the resource scheduling agent generates a construction plan according to the optimal scheme; the coordination / communication agent is used for ensuring efficient cooperation among the agents through a communication protocol and a negotiation mechanism among the agents; the diagnosis report, the optimal scheme and the construction plan are integrated and presented to a bridge manager through a human-computer interaction interface; and collaborative optimization of bridge management and maintenance decisions is realized through continuous feedback and self-learning.

The invention provides an intelligent e-commerce behavior event decision-making method and system fusing multi-source perception, and the method comprises the steps: obtaining a user behavior data set, a commodity attribute data set and an environment context data set through a preset data collection interface, and carrying out the intention recognition processing of multi-source data; generating an intention feature set containing preliminary intention features and refined intention features, then generating an interactive guidance strategy tree containing node branch weights and strategy execution priorities based on the intention feature set, and performing dynamic path adjustment processing on the interactive guidance strategy tree according to a real-time feedback data set to obtain an optimized strategy tree set; and finally, pushing the optimization strategy tree set to a target interaction interface to activate an interaction guide operation, thereby providing personalized and intelligent interaction guide for the user by fusing multi-source sensing data, deeply understanding the intention of the user and dynamically adjusting a decision strategy, and improving the operation efficiency of an e-commerce platform and the satisfaction of the user.

The invention provides a VR scene adaptive rendering method based on AI and multi-modal perceptual interaction, and the method comprises the steps: firstly obtaining a perceptual signal set of a current interaction stage of a user through a multi-modal interaction interface, including user interaction actions, visual attention and scene physical feedback signals, and then analyzing the set to obtain a sensing signal set of the current interaction stage of the user; the method comprises the following steps: generating user concerned area features and scene dynamic sensitive area features, then determining a rendering area priority sequence and a detail retention reference through a rendering resource allocation model based on the user concerned area features and the scene dynamic sensitive area features, and adjusting a resource scheduling rule and a quality control rule of a VR rendering system according to the result. And executing the adjusted rule to generate the current frame of rendering picture, and updating the decision logic of the rendering resource allocation model according to the change trend of the interactive feedback of the user to the current frame of picture and the physical feedback of the scene, thereby realizing the dynamic self-adaption of VR scene rendering, improving the rendering efficiency and quality, and enhancing the user immersion.

The invention discloses a tourism service agent system and method based on a multi-modal large model. The system comprises five parts: a user interaction interface, which is used for receiving a user request and returning a response; the agent center is used for performing intention understanding, task planning and response generation through a multi-modal large language model; and the tool calling module is used for executing specific API business operation. According to the intelligent tourism service system, the work of each module is coordinated through the intelligent agent center, a complete closed loop from user intention understanding to service execution is realized, accurate, reliable, whole-course and personalized intelligent tourism service can be provided, and the problems that a traditional tourism service system is single in function, inaccurate in information and lack of action ability are effectively solved.

The invention discloses a multi-source remote sensing ecological production environment assessment system, and belongs to the field of ecological environment assessment. The system is composed of a data acquisition module, a data processing and fusion module, a generative artificial intelligence core engine, an ecological evaluation and decision support module and a user interaction interface, and all the modules are connected with one another, so that the overall function of the system is realized. According to the method, through a'representation-cognition-semantics' three-layer fusion architecture, the system can surpass traditional data piling, deep integration is carried out on multi-source information from bottom-layer features and spatial relationships to high-layer semantics, so that a complex interaction mechanism among ecological elements is more accurately understood and described, and the system is more efficient and efficient. And the overall cognitive ability and evaluation accuracy of the complex ecological system are remarkably improved. The system is based on a generative artificial intelligence core engine, not only can analyze the current situation, but also can simulate future scene evolution under different ecological management strategies.

The invention relates to the technical field of artificial intelligence and judicial informatization, and particularly discloses a multi-format document intelligent retrieval and semantic association system driven by a large model. Comprising a multi-modal document intelligent analysis module, an intention-driven semantic retrieval module, a knowledge graph enhanced association recommendation module, a retrieval result visualization and interaction module, a reinforcement learning-driven system optimization module and a multi-format document data storage module. According to the method, the multi-format judicial document is intelligently analyzed through a large model technology; the query intention of the user is accurately understood by means of a semantic retrieval technology Semantic association among the documents is deeply mined through the knowledge graph technology; a retrieval result is visually displayed through a visualization and interaction interface; and the retrieval strategy and model performance are continuously optimized according to user feedback by relying on a reinforcement learning algorithm, so that the retrieval efficiency and semantic association capability of the multi-format document in the judicial field are effectively improved, and the development of judicial informatization is promoted.

The invention relates to the field of artificial intelligence and big data processing, and discloses a professional field agent construction method and system based on a multi-modal hybrid expert model and a knowledge graph. The method comprises the following steps: collecting multi-source heterogeneous data such as user behaviors, texts, images, structured data and voices, and vectorizing and coding the multi-source heterogeneous data; performing feature extraction on different modal data and fusing to form unified representation; constructing a hybrid expert network based on a gating mechanism to perform task specialization processing on the fusion representation; introducing a domain knowledge graph and performing semantic enhancement through a graph neural network; on the basis of fusion representation, tasks such as recommendation, intention recognition and question and answer are executed at the same time through a multi-task learning framework; and an output result is fed back through the multi-modal interaction interface, and user feedback is collected to update the model. According to the method, the semantic understanding, task prediction and personalized recommendation capabilities of the model in a complex scene can be improved.

The invention relates to a leather material cutting robot and a cutting method thereof, and belongs to the technical field of material cutting, the leather material cutting robot comprises a human-computer interaction interface, a CAD / CAM system, a multi-mode visual perception unit, a central processing system, a dynamic compensation cutting unit and a quality closed-loop system, and the multi-mode visual perception unit comprises a high-resolution multispectral imaging module and a 3D scanning module. According to the method, the problems that a traditional leather material cutting robot visual recognition system cannot recognize leather thickness changes, material waste is easily caused by subcutaneous defects, natural curling deformation of leather is difficult to adapt, and the edge precision error is large are solved, the rejection rate can be further reduced through multispectral and 3D defect recognition, and the production efficiency is improved. Three-dimensional dynamic compensation enables edge errors to be further reduced, and real-time force control further reduces the occurrence rate of crush damage.

The invention provides a dynamic data traceability method and system oriented to network security, and relates to the technical field of network security and data governance crossing, and the method comprises the steps: carrying out the real-time visual monitoring of a user interaction interface of a data transaction platform, and capturing the visual behavior information related to data calling; extracting feature parameters based on the visual behavior information to obtain a visual feature data set, and performing structured conversion on the visual feature data set to obtain a structured call log record containing visual behavior associated information; based on the structured call log record, extracting a time sequence, a frequency and a spatial distribution feature of a call behavior as basic indexes; a plurality of feature sampling states are dynamically selected in a monitoring time window, and a dynamic feature evaluation set is constructed based on the feature sampling states. According to the invention, the accuracy and controllability of network security protection in a data transaction scene can be improved.

The invention discloses a multi-dimensional multi-physics field coupling analysis platform of a hydrogen fuel cell based on artificial intelligence, and relates to the technical field of hydrogen fuel cells, the platform comprises a user interaction interface module, a multi-physics field model construction module, a data acquisition and preprocessing module, an integration module and an analysis and result output module; an electrochemical reaction model, a temperature field model and a gas and liquid flow model are respectively built through a multi-physical field model building module, the coupling strength among different physical fields is quantified, and the electrochemical reaction model, the temperature field model and the gas and liquid flow model are integrated into a multi-physical field model; physical action parameters such as electrochemical reaction rate, temperature value and the like are associated with time change, spatial distribution and fault conditions, so that the platform can simulate the multi-physical field coupling effect of the hydrogen fuel cell under complex working conditions, and the performance of the fuel cell is analyzed; and a reliable basis is provided for the geometric structure, material selection and operation condition optimization of the fuel cell.

The invention relates to the technical field of voice recognition, in particular to a voice interaction system and method for customer service based on artificial intelligence, and the system comprises a voice input processing module, an intention classification and routing module, a context dynamic adjustment module, a user behavior learning module, a multi-level intention fusion module and a final result module. According to the method, a multi-dimensional feature system is constructed by extracting tone intensity, speech speed frequency and emotional fluctuation amplitude, intention categories, priority weights and confidence scores are generated to realize accurate acquisition of appeals, and dialogue history, context and emotional change dynamic reconstruction path nodes, switching rules and response time sequences are tracked during interaction. Historical behavior mining preference features, habit fusion intention relevance, emergency calculation of an optimal strategy, construction of service steps, resource allocation schemes and execution timelines, adjustment of an interactive interface, a service process and a feedback mechanism according to multi-dimensional analysis, guarantee of differentiated service experience, and improvement of response accuracy and user satisfaction.

The invention discloses a duplex-screen intelligent cabin interaction method and system, and relates to the technical field of intelligent cabin interaction, and the method comprises the steps: collecting user operation behavior data, vehicle state data and environment perception data in real time through a vehicle-mounted sensor group, a man-machine interaction interface and a vehicle bus; establishing a multi-dimensional user data model containing an interaction feature vector, a driving mode matrix and a preference configuration tree; the method comprises the following steps: analyzing user historical interaction data based on an adaptive weighting algorithm, and calculating use frequency weight coefficients of different functional modules; according to the duplex-screen intelligent cockpit interaction method and system provided by the invention, the precision of a user portrait is remarkably improved by constructing a multi-dimensional user data model, personalized interaction experience is realized, and the interface layout and interaction logic can be dynamically adjusted according to a real-time driving scene by adopting a self-adaptive weighting algorithm and a random forest classifier, so that the user experience is improved. The real-time performance and the adaptability of the system are enhanced, and the interaction experience is optimized.

The invention discloses an academic group mining and directional recommendation system for regional natural fund, and relates to the technical field of computers. The academic group mining and directional recommendation system for the regional natural fund comprises a data management system, a knowledge graph module, a mixed recommendation algorithm module, an AI robot module and a user interaction interface module, and a multi-dimensional heterogeneous relation graph, an innovative cold start solution and a lightweight graph recommendation framework are constructed. Accurate mining, intelligent recommendation and efficient management of scientific researchers and projects are realized. According to the method, potential interests and cross-domain association requirements of users can be deeply captured, the problem of data sparsity in a cold start stage is effectively solved, and rapid deployment and real-time recommendation are realized through lightweight design. And powerful technical support and decision basis are provided for reasonable distribution and scientific research and innovation of regional natural funds.

The embodiment of the invention relates to the technical field of data processing, and particularly provides a smart library information retrieval method and system based on AI session interaction. According to the embodiment of the invention, an information retrieval session request initiated by a user through a smart library interaction interface is received; collecting session interaction data containing natural language query content and context association information; performing semantic structuring processing on the session interaction data to generate a session semantic feature set containing an entity relationship network and an intention classification vector; carrying out deep mining on the session semantic feature set by utilizing a debugged retrieval intention understanding model, identifying potential retrieval demands and demand priority ranking, and generating retrieval demand feature vectors; and on the basis of library collection information in the vector matching intelligent library resource database, generating an information retrieval result set containing resource association degree sorting, and feeding back the information retrieval result set to the interactive interface for visual display. According to the embodiment of the invention, the accuracy and comprehensiveness of information retrieval are improved, and more intelligent and efficient retrieval experience is provided for users.

The invention relates to the technical field of computers, and provides an intelligent interaction guiding method and system based on user intention recognition. According to the embodiment of the invention, deep and comprehensive user interaction analysis is realized; the user demand dynamic state can be accurately captured by acquiring the interaction data set in real time; and context association features and interaction behavior features generated by multi-modal feature extraction provide a rich and meticulous information basis for intention analysis. On the basis, a preset intention recognition rule base is used for carrying out joint intention analysis processing, an intention label set and user portrait features are generated, accurate insight of the user intention is achieved, and then an interaction path guiding strategy is generated and pushed to a target user terminal in real time to update an interaction interface. Therefore, the method and the system can closely meet user requirements, provide personalized operation guidance, remarkably improve man-machine interaction efficiency and user operation accuracy, and enhance the intelligent service level of an intelligent factory.

The invention relates to the technical field of unmanned aerial vehicle cluster navigation, and discloses an unmanned aerial vehicle cluster navigation method based on man-machine interaction. The method comprises the steps that cluster task parameters and environment constraint conditions input by an operator are efficiently received through a multi-modal interaction interface, the cluster task parameters comprise a target point coordinate set and formation form identification, and the environment constraint conditions cover no-fly zone coordinates and meteorological interference levels. And the system calls a pre-stored topological relation template according to the formation form identifier to generate an initial track, completes space conflict detection in combination with the no-fly zone coordinates, and outputs a corrected track point sequence. And inputting the meteorological interference level into a dynamic anti-interference model to calculate a course correction amount, and superposing the course correction amount to a corrected track point sequence to generate an anti-interference navigation instruction set. And acquiring position data of the unmanned aerial vehicle in real time to calculate a trajectory deviation degree, triggering a manual intervention request if the trajectory deviation degree exceeds a dynamic threshold value, calling a correction instruction, fusing to generate a hybrid control strategy, and distributing the hybrid control strategy to each node of the cluster to realize reliable man-machine collaborative navigation.

The invention discloses a pulsed neutron generator control system based on LabVIEW, and the system comprises a neutron generator industrial personal computer which operates a virtual human-computer interaction interface developed based on LabVIEW; the console core board carries a DSP main control chip and is embedded into a real-time operating system; the driving sampling board is connected with the console core board and is integrated with a signal conditioning circuit; the neutron generator industrial personal computer communicates with the console core board through a Modbus protocol, and controls and drives the sampling board to output control signals of the three independent power supply ion sources, the storage and the acceleration pole to the neutron tube; wherein the console core board generates three paths of PWM signals with the PWM frequency of 2.5 kHz and the step length of 8191, and the three paths of PWM signals are converted into analog control signals through the driving sampling board. According to the control system, the PWM control precision is greatly improved, the voltage control precision is improved to 0.012% (100% higher than that of a conventional scheme) through the combination of the 8191 step length (13-bit resolution) and the 2.5 kHz frequency, and the neutron yield fluctuation is controlled within + / -1.5%.

The application discloses a multimodal interaction method, device, controller, system, automobile and storage medium. The method comprises the following steps: determining a current interaction dialogue according to a current interaction voice at an interaction time; determining a current scene image and current scene data corresponding to a current interaction interface corresponding to the interaction time; adopting a multimodal recognition model to perform multimodal recognition on the current interaction dialogue, the current scene image and the current scene data, and determining a target control instruction; and executing the target control instruction to complete a human-computer interaction operation. The method can guarantee the output efficiency and accuracy of the target control instruction, reduce the complexity of customizing templates, rules and associations and other complex control logics in the development process, and improve the adaptability and generalization ability of voice interaction.

The invention discloses an AI automatic editing method and related equipment, and the method comprises the steps: obtaining a video prototype template selected by a user, prompt information inputted by the user, and original materials uploaded by the user through a user interaction interface, and calling a language large model to generate a structured video script; performing association degree matching on the structured script and the original material through a target detection model, and screening the original material according to a matching result and a quality scoring model to obtain an original video clip; performing background music matching according to the video script to obtain background music, generating voice dubbing and a flower-character chartlet according to the video script, generating video subtitles according to the voice dubbing, performing time axis alignment on each video media element, and synthesizing into a finished video. According to the embodiment of the invention, full-process automatic processing from script generation to video synthesis can be realized, and a high-quality finished video meeting user requirements can be efficiently output. The method can be widely applied to the technical field of automatic editing.

The embodiment of the invention provides a content generation method and a multi-modal canvas system, which are used for analyzing user intention in the same canvas scene and generating content required by a user. The method comprises the steps that a user interaction interface is displayed, wherein the user interaction interface comprises a canvas area; receiving a user interaction event triggered by a user in the canvas area, and identifying a user intention and event content of the user interaction event; generating a plurality of target agents for executing reasoning tasks of the user interaction event; and executing a reasoning task of the user intention and the event content of the user interaction event by utilizing the plurality of target intelligent agents, generating target content information, and displaying the target content information in the canvas area.

The present invention discloses a charging and discharging control method and system for an electric vehicle based on virtual synchronization, and relates to the technical field of virtual synchronization. The method includes: establishing connection between a power grid and the electric vehicle, and acquiring a charging and discharging operation demand; acquiring, according to the charging and discharging operation demand, a corresponding control instruction and constraint condition, and executing a charging and discharging operation; and providing a human-computer interaction interface for measuring and settling charging and discharging energy, along with authentication. The present invention achieves efficient and coordinated charging and discharging control, precise measurement and convenient authentication, and improves availability and reliability of the system.

The invention provides a data asset display analysis method and system based on data visualization, and belongs to the technical field of data asset display analysis. Then, carrying out visualization dimension mapping processing to obtain a visualization dimension set comprising a structure dimension, an association dimension and a circulation dimension, and constructing a multi-level display template comprising a basic display layer, an association display layer and a dynamic display layer according to the visualization dimension set; according to the method, the multi-level display template is subjected to interaction adaptation processing according to user analysis requirements to generate a visual interaction interface, operation track data of a user in the visual interaction interface is tracked, the multi-level display template is adjusted based on the operation track data, the visual interaction interface is updated, and comprehensive, visual and interactive display analysis of data assets is achieved.

The invention provides an intelligent customer service robot based on multi-modal data fusion and knowledge graph enhancement and a construction method thereof. The method comprises the following steps: constructing a data layer of the intelligent customer service robot, wherein the data layer comprises a knowledge graph and a weavate vector database; constructing a model layer of the intelligent customer service robot, wherein the model layer comprises a question classification model, a knowledge graph query engine, a vector retrieval module and a large model interaction interface; constructing an application layer of the intelligent customer service robot, wherein the application layer comprises a Web end interaction interface, an API service and a management background; and constructing access links of the data layer, the model layer and the application layer. According to the method, structured query of the knowledge graph and semantic retrieval of the vector database are communicated, a'accurate matching + semantic generalization 'mixed question and answer mode is realized, and the answer quality of open questions is improved.

The invention discloses an agent configuration method and device based on front-end interaction and a medium, and relates to the technical field of computers.The method comprises the steps that a user interaction behavior is received through a front-end interaction interface, the user interaction behavior is analyzed, and a corresponding response instruction is generated; executing the response instruction, creating a plurality of agent nodes, and configuring corresponding role information; determining a task dependency relationship between the agent nodes, and constructing an agent node relationship graph through a preset task execution rule; receiving and analyzing a to-be-executed task, extracting required agent role information, determining to-be-executed agent nodes, and determining a to-be-executed sequence corresponding to the to-be-executed agent nodes according to the agent node relation graph; and calling the agent models corresponding to the to-be-executed agent nodes in sequence, executing the to-be-executed task, and updating the state parameters. Through deep fusion of front-end visual interaction and automatic process arrangement, the intuition and efficiency of the configuration process are improved.

The invention provides a household small electric appliance diagnosis system based on AR imaging and AI interaction, which relates to the technical field of intelligent household appliance intelligent diagnosis and comprises a multi-mode intelligent sensing framework, a modular AR detection accessory, an AI diagnosis analysis center and a human-computer interaction interface. According to the modular AR detection accessory, the sensor module is rapidly replaced through the magnetic type universal interface base, the requirement for collecting temperature, circuit, sound and other multi-mode data is met, the hardware adaptability is remarkably improved, the modular AR detection accessory has the functions of low power consumption and efficient power supply, a battery is arranged in the base, reverse wireless charging is supported, and the reliability is high. The problem of endurance of a high-power-consumption module is solved, a modular AR detection accessory is combined with an AR terminal through a magnetic type sensor module, fault three-dimensional coordinates are superposed on real equipment in real time, a user can visually check internal problem points, a mixed reality operation table supports gesture, voice and eye movement control, the operation threshold is lowered, and the operation efficiency is improved. According to the invention, the user is directly guided to carry out precise maintenance through the AR marking system.

The invention discloses an emotional man-machine interaction method, device and equipment based on emotion recognition and a computer readable storage medium. The method comprises the steps that first modal action data, second modal facial expression data and third modal physiological parameter data of a user are synchronously collected; processing the first modal motion data and a preset standard emotion-motion template through a posture estimation and dynamic time warping algorithm to generate a motion evaluation score; inputting the action evaluation score, the second modal facial expression data and the third modal physiological parameter data into a preset multi-modal fusion model for processing to generate a quantized user emotion level; based on the quantized user emotion level, determining an interface adjustment parameter and an emotional feedback text; and applying the interface adjustment parameter and the emotional feedback text to the current human-computer interaction interface. The emotional man-machine interaction method based on emotion recognition has the advantages of being accurate in emotion recognition, intelligent in interaction, personalized and the like.

The invention relates to the technical field of communication equipment operation and maintenance, in particular to a serial port equipment firmware upgrading method and system. The serial port equipment firmware upgrading method comprises the steps that an upgrading task instruction issued by a remote management platform is received, and after equipment identity verification and upgrading file integrity verification are executed, system protection measures are started; creating a security isolation sandbox environment, forbidding a high-risk function module in a script execution environment, and defining addressing parameters of target serial port equipment; standard scripts are loaded, and serial port read-write, file operation and state reporting type security interaction interfaces are injected; calling a mode switching function of the standardized script, so that the serial port equipment is switched to a firmware upgrading mode from an operation mode; cyclically calling a data transmission function of the standardized script to transmit firmware data in blocks, and synchronously implementing timeout monitoring; and after upgrading is completed or abnormal interruption occurs, the security isolation sandbox environment is destroyed, the original business is recovered, and an upgrading result is reported to the remote management platform.

The invention provides a fault diagnosis method, diagnosis device and fault diagnosis equipment, and relates to the technical field of fault diagnosis, and the fault diagnosis method comprises the steps: obtaining test firmware corresponding to the model of a to-be-measured force plate in response to the model selection of the to-be-measured force plate, and displaying a test interface corresponding to the to-be-measured force plate; and in response to a detection operation for the to-be-measured force plate, running the test firmware, and determining the working state of the to-be-measured force plate. According to the method, efficient fault diagnosis is realized through the automatic test process and the user interaction interface, the efficiency and accuracy can be improved, and manual dependence is reduced.