302 results about "Background data" patented technology

The invention relates to the technical field of e-commerce data processing, in particular to an e-commerce sales platform background data management method and system. The method comprises the following steps: S1, collecting a commodity dynamic data stream, a user behavior event stream and a promotion strategy stream in real time, and generating a standardized data stream through time sequence alignment; s2, constructing a dynamic coupling data cube; s3, executing a real-time decision: in response to the payment request, selecting an inventory distribution or replacement commodity pushing strategy based on a commodity-user coupling matrix value; in response to the resource overload state, triggering a resource scheduling strategy; and S4, dynamically adjusting calculation parameters of the coupling matrix according to decision execution feedback. By solving the problems of real-time standardization processing of multi-source heterogeneous data and real-time coupling of dynamic inventory and user behaviors, the data processing capacity, inventory distribution efficiency and recommendation accuracy of the platform are remarkably improved.

The invention relates to the technical field of semantic processing, in particular to a context-aware SQL (structured query language) generation method based on table field semantic enhancement, which comprises the following steps of: acquiring financial management and investment combination data of a user and mode information of a background database, constructing a mixed semantic index database, receiving natural language query input by the user, and generating a query result. Performing intention judgment on the query by utilizing the lightweight intention classification model, and if the intention is judged to be matched, calling a parameterized SQL template bound with the query intention and filling parameters to generate a final SQL query; if it is judged that the query intention is an exploration type intention, executing a two-stage SQL generation process, including generating an SQL skeleton according to the query intention, performing target type field recall based on the SQL skeleton, and filling the recalled field into the SQL skeleton to generate a final SQL query; and monitoring the execution performance of the final SQL query, and updating the query popularity metadata and the calculation cost metadata. According to the method, the SQL generation efficiency is improved through intelligent shunting and self-optimization.

The invention relates to the technical field of soil remediation management, in particular to a method and system for soil remediation and digital management, and the method comprises the steps: data construction: fusing multi-source monitoring soil environment parameters with space-time background data such as a GIS layer and a meteorological time sequence to form a data set; state quantification: outputting a comprehensive state index for quantifying restoration urgency and complexity through the soil health assessment model; scheme generation: matching the restoration target library and the resource library, and generating a digital restoration scheme containing an expected state trajectory through an optimization algorithm; closed-loop control is carried out, feedback data comparison tracks are continuously collected, if the deviation exceeds a threshold value, the index is recalculated, the scheme is dynamically adjusted, and the system comprises a data construction module, a state quantification module, a scheme generation module and a closed-loop control module and executes the method. According to the method, the data reliability and evaluation scientificity are improved, the scheme adaptability is guaranteed, dynamic and controllable remediation is realized, and digital and efficient management of soil remediation is promoted.

The invention relates to the technical field of image data processing, and discloses an AI target change detection method fusing a time sequence remote sensing image, which comprises the following steps of: calculating a difference information entropy value of a remote sensing image on a satellite-borne edge calculation unit, and comparing the difference information entropy value with a trigger threshold value; only when the information entropy value is higher than the threshold value, the change area is extracted to form an incremental information packet to be transmitted to the ground; and after analyzing the incremental information packet, the ground station generates an instruction according to the identified environmental interference characteristics and regional stability, feeds back the instruction to the satellite-borne unit, and bidirectionally adjusts a trigger threshold value. According to the invention, an information screening decision is preposed to a data generation source, so that invalid transmission of massive invariable background data is avoided; therefore, the acquisition delay of the key change information is obviously reduced; the established satellite-ground closed-loop feedback mechanism enables the whole monitoring method to continuously optimize the judgment standard during use, and the applicability and reliability of the method are improved.

The invention belongs to the technical field of virtual automobile exhibition, and particularly relates to a virtual automobile exhibition system based on digital twinning. The system comprises a digital twinning construction module which generates a lightweight model and supports first-person visual angle dynamic updating; the user behavior analysis module is used for mapping data such as a sight track into a weighted directed graph, and predicting vehicle types and configuration requirements by using a multi-head graph attention network; the personalized configuration selection module is used for generating a configuration scheme in combination with digital twinborn parameters; the virtual test driving module is used for providing immersive experience based on the configuration scheme and the scene; and the background data analysis module integrates the data to generate a user portrait so as to optimize the exhibition content. According to the system, dynamic virtual-real mapping, accurate demand prediction and data-driven intelligent exhibition are realized, and the user interaction depth and the car purchase efficiency are improved.

The invention relates to an underwater visible light signal recovery method based on transfer learning, and aims to solve the problems of signal noise, distortion and communication performance reduction caused by disturbance of water turbidity, flow velocity, ambient light intensity and the like on an underwater visible light communication (UVLC) system. In combination with transfer learning and a generative adversarial network (GAN), data are acquired through a self-developed hardware platform, background data are generated through MATLAB simulation, simulation and real image features are fused by using a conditional generative adversarial network (cGAN) to generate simulation data, signal recovery capability is trained by using a U-NetGAN model, and finally the system is deployed at a receiving end. Compared with the prior art, the scheme overcomes the problems that traditional modulation is poor in adaptability under disturbance of water turbidity, flow velocity and the like and is difficult to deal with a complex underwater environment; the defects that a deep learning method depends on large-scale data and cross-scene generalization is weak are overcome. Through the combination of transfer learning and GAN, the UVLC system communication performance is significantly optimized, the delay is low, the complexity is low, and actual deployment requirements are better met.

The invention provides a safety risk control method for geological storage of carbon dioxide and electronic equipment. A distributed optical fiber sensing system is arranged in at least one injection well of the target sealing and storage area in the axial direction of a shaft and penetrates through a main cover layer and a reservoir; the method comprises the following steps: acquiring background data through a distributed optical fiber sensing system, and establishing a multi-parameter baseline model including a temperature field, a strain field and background noise; temperature, strain and sound wave vibration signals are collected in real time, and key features are extracted; the key features extracted in real time are compared with a preset risk feature library, the types of risk events are identified, and the identified risk events are graded according to the spatial range and intensity of the abnormal signals; and according to the type and the grade of the risk event, generating and executing a corresponding control instruction. According to the embodiment of the invention, the optical fibers are distributed in the whole area along the shaft and the target stratum, a three-dimensional monitoring network covering the sealing body is constructed, and the hysteresis quality of traditional point type measurement and periodic exploration is overcome.

The invention relates to the technical field of communication, and discloses a measurement and control communication parameter transmission state monitoring system, which comprises a data acquisition and adaptation module which is responsible for acquiring an original parameter data stream by measurement and control equipment, performing unified formatting processing on the original parameter data stream and then sending the original parameter data stream to a state optimal estimation module. A technical scheme of constructing a state space model at an edge end, performing optimal state estimation on original measurement and control parameters in combination with a Kalman filter, and performing statistical distribution deviation quantification on a filtered residual sequence by using KL divergence is adopted, a system high-fidelity operation state is extracted from strong noise background data, and progressive weak abnormity is early warned in advance and accurately. Compared with a scheme of carrying out fixed or simple statistical threshold alarm on an original measurement value, the problems that state misjudgment is caused by measurement noise interference, progressive performance degradation cannot be effectively sensed, fault discovery is lagged and the early warning capability is insufficient are solved.

The invention discloses a water regimen data acquisition dual-machine redundancy method and system, and the system comprises a main machine and a standby machine which are directly connected through an independent heartbeat interface. The main machine periodically sends heartbeat messages and local network configuration information to the standby machine through a heartbeat interface; and the standby machine monitors heartbeat in real time, judges that the main machine is abnormal once not receiving the heartbeat within a preset time, automatically takes over the IP address of the main machine, actively sends an address resolution protocol message according to pre-stored network configuration information so as to quickly update a forwarding table of the network equipment, immediately switches the state of the standby machine to be the main state, and synchronizes the state to a database. According to the method, automatic sub-second fault switching is achieved, the risk of key data loss is greatly reduced, continuity and integrity of water regimen telemetering data are guaranteed, meanwhile, the operation load of a background database is remarkably reduced through a main and standby mode, and the reliability of water regimen telemetering is improved. The problems that the load of the database is too heavy and automatic seamless switching of network channel data acquisition cannot be realized are solved.

The invention discloses a warranty service processing method and device, equipment, a storage medium and a product, and relates to the technical field of text generation, and the warranty service processing method comprises the steps: obtaining target background data of a warranty application, and based on a large language model, recognizing warranty application elements in the target background data, and filling the obtained target warranty elements into a warranty application template to obtain a target warranty text, and visually displaying the target warranty text to enable a user to preview the warranty text, and submitting the target warranty text to a warranty service system to complete warranty service processing. According to the method, the client is assisted in filling the form through the background data, the corresponding warranty text is generated and visually displayed, so that the user does not need to manually fill tedious and error-prone warranty application elements and can preview the warranty text before submission, repeated warranty text modification, submission and approval processes are avoided, and the user experience is improved. Therefore, the processing efficiency of the warranty service is improved.

The invention relates to the field of photovoltaic product carbon footprint accounting, and discloses a data screening and evaluation method and system for supporting development of a photovoltaic product carbon footprint background data set based on an environmental assessment file. According to the method, a multi-level structured environmental assessment file label system is constructed, a multi-dimensional data source quality evaluation index is established, a nonlinear confidence enhancement scoring function, a multi-level weighting mechanism and a key index elimination mechanism are provided, and a data source quality comprehensive evaluation scheme is formed. In the data extraction stage, a data category division scheme based on the key composition of photovoltaic products and a harmonic enhanced unit standardization processing method are adopted. Meanwhile, a multivariate cross check mechanism fusing industry reference value check and triple balance check is constructed, a three-dimensional data quality scoring model is introduced, and a data quality comprehensive evaluation system is formed. According to the application, the carbon footprint data quality of the photovoltaic product is remarkably improved, and data support is provided for industrial carbon accounting.

The invention discloses a near-shore disaster-bearing body disaster-causing path tracing method based on a digital-analog experiment, and relates to the technical field of ocean dynamic disaster simulation, the near-shore disaster-bearing body disaster-causing path tracing method comprises the following steps: determining ocean dynamic disaster characteristics of a near-shore research area, integrating multi-source historical disaster data, real-time monitoring data and disaster-bearing body background data, and constructing a time-space association database; and based on a three-dimensional ocean and third-generation ocean wave mode, an offshore storm surge-ocean wave coupling numerical mode is established and verified. According to the method, a storm surge-sea wave coupling numerical mode is constructed, multi-disaster-type nonlinear interaction is comprehensively considered, an energy conservation equation is introduced to quantify generation, transmission and dissipation processes of disaster energy, limitation of a traditional single-disaster-type linear model is solved, real-time feedback of a disaster-bearing body three-dimensional dynamic model is combined, and the disaster-bearing body three-dimensional dynamic model is optimized. A closed energy-damage association mechanism is formed, the tracing accuracy of a disaster chain type propagation path is remarkably improved, and it is ensured that recognition of key nodes and dominant paths better conforms to physical reality.

The invention relates to the technical field of engineering management informatization, in particular to a BIM visualization method and device based on a UE engine, and the method comprises the following steps: importing a BIM model into a UE5 engine, and carrying out scene rendering; establishing association between background data of the BIM model and job task progress data in the P6 platform; and according to the job task progress data of the P6 platform, performing project progress visual display on the BIM model. The method has the advantages of real-time rendering, vivid effect, blueprint type low-threshold development and the like.

The invention discloses an in-vitro liquid level measurement method and device based on millimeter wave radar and a medium, and relates to the technical field of liquid level measurement, and the method comprises the steps: collecting geometric parameters of a container, building a container coordinate system, and forming static background data; the millimeter wave radar array is controlled to radiate millimeter wave signals in sequence, a receiving channel receives reflection echoes, amplification, frequency mixing, filtering and sampling processing are carried out, and array time sequence data are obtained; according to the array time sequence data, generating a distance direction frequency spectrum data set, combining static background data to carry out background deduction, executing an incident direction estimation algorithm, obtaining scattering point cloud under a container coordinate system, and generating a liquid level two-dimensional contour; based on the two-dimensional contour of the liquid level and the geometric parameters of the container, effective bottom surface grids are screened, the estimated value of the liquid volume in the container is obtained and converted into the equivalent liquid level height, and the final liquid level height is obtained. The two-dimensional fluctuation form of the liquid level is finely described, and the liquid volume and liquid level height measurement precision is improved.

The invention relates to the technical field of satellite communication, and discloses an efficient encoding and decoding and distribution transmission method for satellite image data, which comprises the following steps of: acquiring satellite epoch parameters, estimating a downlink channel capacity sequence, decomposing the image data into a basic feature code stream and a background residual code stream, and distributing a transmission priority, and mapping the basic feature code stream to the most significant bit of the modulation symbol, mapping the background residual code stream to the least significant bit of the modulation symbol, and implementing nonlinear displacement stretching on the coordinate of the constellation point where the modulation symbol is located according to the carrier frequency shift change rate. A core semantic bit phase tolerance boundary is expanded by compressing a background data judgment space, high-fidelity transmission of key image features in a severe phase distortion environment is ensured, and the information transparent transmission capacity in a high-dynamic link is improved.

The invention belongs to the technical field of target tracking, and provides a water surface target tracking method based on 4D millimeter wave radar and unmanned aerial vehicle remote sensing image fusion, electronic equipment and a storage medium. The method comprises the steps of data acquisition, preprocessing, dynamic foreground extraction, foreground optimization, radiation feature extraction, target identification, background point cloud elimination, motion data extraction, position prediction and instruction generation. Through alignment processing and filling processing, a basis is provided for foreground extraction, and the foreground analysis effect is improved; through dynamic foreground extraction, noise filtering and contour optimization, most background data irrelevant to a tracking target are reduced, and the input data quality of a recognition model is improved; through the improved Faster-RCNN network, the structure of the recognition model is optimized, and the recognition speed is increased; through background point cloud elimination and tracking object motion data extraction, the point cloud volume is reduced, and the input data dimension is increased.

The embodiment of the invention provides a method and a device for determining an inclination angle and an azimuth angle of a photovoltaic power station. The method comprises the following steps: acquiring background data of the photovoltaic power station; based on the background data, calculating the daily total radiation quantity corresponding to any inclination angle assumed value in the inclination angle initial range, and determining the inclination angle assumed value corresponding to the maximum daily total radiation quantity as a reference inclination angle; determining a new inclination angle range by taking the reference inclination angle as a center, and dividing the azimuth angle initial range to obtain three azimuth angle subareas; for each azimuth subarea, performing multi-target optimization on the total income and the unit income by using a Monte Carlo-gradient descent hybrid algorithm, and outputting an optimal inclination angle and an optimal azimuth angle corresponding to the azimuth subarea; and respectively calculating an optimal inclination angle corresponding to each azimuth subarea and a yield rate corresponding to the optimal azimuth angle, and obtaining and outputting the inclination angle and the azimuth angle corresponding to the highest yield rate. The optimal inclination angle and azimuth angle are accurately determined for the photovoltaic power station, and the power generation income of the photovoltaic power station is effectively improved.

The invention discloses an emergency linkage and emotion recognition integrated household intelligent guard system and method, and relates to the technical field of Internet of Things, artificial intelligence and emergency response, the system comprises the following components: a front-end sensing device, an edge AI processing unit, a voice broadcast interaction module, a remote linkage module and a background data platform; by integrating the front-end sensing device and the edge AI processing unit, multi-dimensional real-time monitoring of human body behaviors, emotional states and environment information is achieved, the abnormal behaviors and emotional states of a user can be accurately recognized by the system through the behavior recognition module, the emotional analysis module and the multi-modal fusion module, and the user experience is improved. And active care and family interaction are carried out through the voice broadcast interaction module, and the remote linkage module is triggered to inform family members or an emergency platform if necessary, so that a closed-loop intervention mechanism is formed, and the intelligent level and the response speed of family safety monitoring are effectively improved.

The invention provides an intelligent micro-maintenance system for concrete test blocks, which comprises a drawer type storage cabinet, an intelligent transportation robot and a maintenance subsystem, the maintenance subsystem comprises an intelligent control module, the drawer type storage cabinet performs three-dimensional modeling, real-time maintenance monitoring and calculation to obtain a target temperature parameter and a target humidity parameter; the automatic digital recording module is used for binding test block native information and automatically recording process information; the intelligent transportation module is used for carrying out intelligent identification, safe grabbing, carrying and intelligent putting of the test blocks by utilizing an intelligent transportation robot; the remote supervision module is used for performing data mapping at the background and performing visual display at the front end to calculate the optimal operation scheme of the equipment; and the credible tracing module constructs and links a multi-primary-key database table and a whole-process individual file. The maintenance environment consistency can be greatly improved, full-link unmanned management and digital recording are realized, the traditional labor burden and misoperation risk are greatly reduced, the equipment energy consumption is optimized, and the cost is reduced.

The invention discloses a drainage system pipeline liquid level monitoring equipment optimization method and system under a rainfall-free working condition, and belongs to the technical field of monitoring equipment layout. The method comprises the following steps: carrying out interpolation perfection on jump and missing of monitoring data by utilizing a long-short-term memory artificial neural network; obtaining pipe network background data, and forming a pipe network generalization graph based on pipe network topology logic; a liquid level long-time-sequence typical value is selected to calculate the pipe network typical working condition flow velocity and the lag time between every two monitoring points; and calculating the correlation of the monitoring points by adopting a distance correlation coefficient, and recommending optimizable equipment in combination with a significance test. The system comprises a data governance module, a pipe network generalization module, a flow velocity and lag calculation module and a correlation calculation module, and functions of all the steps of the method are correspondingly achieved. The method realizes equipment optimization layout based on the existing monitoring data, reduces the number of equipment, reduces the operation and maintenance cost, has the advantages of high reference value, easy execution and wide application range, and is suitable for an urban drainage system monitoring equipment layout optimization scene.

The invention discloses an interpretability prediction method, system and device and a computer readable storage medium, and relates to the technical field of artificial intelligence, and the method comprises the steps: obtaining an input sample and user background data according to a prediction result interpretation request in response to the prediction result interpretation request, the input sample comprises a plurality of sample features and corresponding feature values; inputting the input sample into a pre-trained small prediction model to obtain a prediction result; determining a local contribution degree of each sample feature to a prediction result, and screening key sample features according to the local contribution degrees; and generating cue words based on the key sample features and the user background data, inputting the cue words and the prediction result into a large language model, and outputting to obtain a natural language interpretation text for the prediction result. According to the method, the understandability of interpretable expression of the model prediction result is improved.

The invention provides a POS application security signature system and method based on cloud service. The system architecture is clearly divided into a front-end service area and a high-security trusted area. The front-end service area is deployed in a special network management area which is logically isolated from the Internet and comprises a Web management background and a Web management background database; the high-security trusted area is a trusted environment, and an application signature server, an application signature server database and a hardware security module are deployed in the high-security trusted area. An application developer accesses the system through a controlled client environment. According to the method, responsibility separation of a submitter, a security officer and a key administrator is realized through role-based access control, hierarchical strong identity authentication is adopted, and a rigorous process is followed; a submitter verifies the hash of a file and then creates a task, the task data is synchronized to a high-security credible area after two security officers approve the task independently in sequence, and two key administrators execute dual control to start an HSM key to complete signature. The whole process operation is recorded in an auditing log which cannot be tampered. According to the invention, automation, high security and compliance of the cloud signature process are realized.

The invention discloses a crawling detection robot steel wire rope data acquisition and transmission optimization method and system, and the method comprises the steps: building a specification parameter-acquisition strategy mapping model based on adaptive steel wire rope specification parameters and a preset damage grade threshold value, and setting an acquisition frequency, a transmission connection parameter and a verification rule. After the robot is started, probe waveform and encoder position data are read in real time, acquisition frequency is dynamically adjusted, key defects and conventional background data are classified and marked, and position indexes are associated to generate original data blocks. Different types of data are packaged after being subjected to hierarchical compression and are transmitted to an upper computer in batches through a remote link, a check code is synchronously sent, and complete transmission or local retransmission is triggered according to a check result. The upper computer analyzes data, restores waveform and position information, automatically identifies defect points, generates alarm details and corrects time information, and supports real-time playback and report generation. The method enhances the comprehensive detection performance of the robot.

The invention provides a ground penetrating radar deep learning YOLO format sample automatic labeling method, comprising the following steps: S1, saving or saving road hidden disease ground penetrating radar artificial interpretation results in a unified data format, each ground penetrating radar data corresponding to an artificial interpretation result file; s2, reading ground penetrating radar data and corresponding artificial interpretation results, sequentially retrieving starting point coordinates and terminal point coordinates of each disease in the artificial interpretation results in the ground penetrating radar data, and delineating a ground penetrating radar data space corresponding to the road hidden disease; s3, taking a ground penetrating radar data space where the disease is located as a center, properly reserving surrounding ground penetrating radar data as a sample background, and intercepting disease data and surrounding background data as disease sample data; s4, self-adaptive gain adjustment is carried out; and S5, carrying out normalization [0 < 1 >] on the whole sample data space, calculating central point coordinates (x, y) of the disease and width and height of the central point coordinates, and automatically generating a ground penetrating radar deep learning sample conforming to a YOLO (Yttrium-Learning-Oriented Yttrium-Learning-Oriented Yttrium-Learning-Oriented Yttrium-Learning-Oriented Yttrium-Learning-Oriented) format.

Systems and methods provide for optimizing video review using motion recap images. A video review system can identify background image data of a video clip including an amount of motion satisfying a motion threshold. The video review system can generate foreground mask data segmenting foreground image data, representing a moving object in the video clip, from the background image data. The video review system can select a set of instances of the moving object represented in the foreground image data. The video review system can generate a motion recap image by superimposing the set of instances of the moving object represented in the foreground image data onto the background data.

This application is directed to data validation and refresh in an electronic device having a memory device. The memory device receives an inquiry for a validity condition of a page of the memory device, which includes a plurality of memory cells that store two consecutive data items and correspond to two nominal threshold voltages. In response to the inquiry, the memory device selects a first readout voltage and a second readout voltage between the two nominal threshold voltages, and applies the first readout voltage and the second readout voltage to read the plurality of memory cells and generate first readout data and second readout data, respectively. An error rate of the page is determined based on the first readout data and the second readout data, and in some embodiments, further used to determine whether an error correction process or a background data refresh need to be implemented on the page.

The present invention relates to the technical field of data security storage, and discloses a cross-border e-commerce background data security storage method and system, the method comprising: collecting cross-border e-commerce background data of an e-commerce transaction area, and identifying non-compliant data in the cross-border e-commerce background data using transaction compliance rules of the e-commerce transaction area; the e-commerce transaction area where the seller is located adopts homomorphic encryption and symmetric encryption to encrypt the compliant data and non-compliant data in the cross-border e-commerce background data respectively, and transmits the encrypted ciphertext to the server of the e-commerce transaction area where the buyer is located; the server of the e-commerce transaction area where the buyer is located stores the encrypted ciphertext, and performs data analysis processing on the stored encrypted ciphertext. The present invention identifies non-compliant data based on the data acquisition method, and adopts different encryption methods for encryption, thereby realizing cross-border e-commerce background data encryption processing of multiple security protection standards, and cross-border transmission and storage of encrypted ciphertext.

This specification discloses a data processing and visualization method, apparatus, medium, and device, which relate to the computer technology field. The method includes selecting a data platform to acquire source data of a target company, organizing the source data and loading it into a data system as a source database table, performing primary data operations to process the source data into target data, performing secondary data operations to process the target data into value-added data, performing tertiary data operations to process related data into graphical data, and performing data visualization to render the graphical data into a visualization diagram. The method of the present invention at least partially solves the problems of inability to timely and completely acquire source data and inability to effectively utilize source data without processing it, thereby improving data processing efficiency, increasing the accuracy of data analysis of the target company through data modeling, and automatically combining background data with front-end displays such as panel interfaces through data visualization, thereby improving the effectiveness of data presentation and the availability of the data system.

The application discloses a nearshore disaster-bearing body disaster-causing path tracing method based on digital-analog experiments, relates to the technical field of ocean dynamic disaster simulation, determines the ocean dynamic disaster characteristics of a nearshore research area, integrates multi-source historical disaster data, real-time monitoring data and disaster-bearing body background data, and constructs a time-space correlation database; based on a three-dimensional ocean and a third-generation sea wave model, a nearshore storm surge-sea wave coupling numerical model is established and verified. Through the construction of the storm surge-sea wave coupling numerical model, the present application comprehensively considers the nonlinear interaction of multiple disasters, introduces an energy conservation equation to quantify the generation, transmission and dissipation process of disaster energy, solves the limitations of traditional single-disaster linear models, and combines the real-time feedback of the three-dimensional dynamic model of the disaster-bearing body to form a closed energy-damage correlation mechanism, significantly improves the tracing accuracy of the disaster chain propagation path, and ensures that the identification of key nodes and dominant paths is more consistent with physical reality.

The invention discloses a method and device for a webpage component to obtain background data, computer equipment and a storage medium. Specifically, the method comprises the following steps: receiving a data request of a front-end webpage; acquiring corresponding data of a background through an event bus according to a subscription theme of the data request; and distributing the data to a corresponding component of the front-end webpage. Through the method, the event bus can be used as a medium to provide background data for the components of the webpage end, and can be used as the components of the webpage end to uniformly send requirements to the event bus, so that corresponding data feedback is returned, and convenience and unification are realized.