836results about How to "Improve compliance" patented technology

The invention belongs to the technical field of electric power data security management and intelligent question answering, and particularly relates to an electric power data security policy large model question answering system and method based on relation pooling. The system comprises a power data security policy knowledge base, a language model, a question processing module, an answer generation module and a user output module. Data of the electric power data security policy knowledge base comes from an electric power data security policy file; the language model converts a natural language problem into a structured query for knowledge base retrieval; the question processing module retrieves policy terms related to the natural language question to serve as retrieval results; the answer generation module generates a final answer according to the natural language question and a retrieval result of the knowledge base; by introducing the intelligent question-answering system combining the large language model and the knowledge base, the problems of low efficiency, inaccurate interpretation, incapability of dynamically updating and the like in the existing power data security policy query and management are solved.

The invention provides a security risk detection method and device for text graph large model generation content, and the method comprises the steps: selecting a test category according to a test parameter based on a preset test database, and matching a corresponding data set from the test database according to the test category; inputting the keywords in the data set into the tested large model in batches according to the format of forward cue words; performing content security detection on a corresponding picture or video image generated by the detected large model according to the input cue word; performing watermark identification detection on a corresponding picture or video image generated by the detected large model according to the input cue word; and analyzing to obtain a detection report according to the content security detection result and the watermark identification detection result. According to the test database, the risk of the large model system is externally assessed based on the characteristics of the input prompt word, the content annotation and the output video content, and the accuracy and effectiveness of the detection and assessment method are improved.

The invention discloses an intelligent rehabilitation treatment management system and method based on big data, and relates to the technical field of intelligent management. During operation of the system, rehabilitation-related data of an orthopedic patient is collected, real-time data is obtained through intelligent wearable equipment and a sensor, the pain and fatigue state of the patient is monitored, preprocessing is carried out, and the patient is subjected to rehabilitation treatment; the method comprises the following steps: analyzing collected data, monitoring the rehabilitation progress of a patient in real time, calculating to obtain a comprehensive rehabilitation progress evaluation index Etotal, comparing the comprehensive rehabilitation progress evaluation index Etotal with a preset state threshold value M and a second preset state threshold value N to generate a personalized rehabilitation scheme, and remotely monitoring rehabilitation data of the patient by a doctor so as to obtain a personalized rehabilitation scheme. According to the method, the rehabilitation plan and the training progress of a patient can be checked through a mobile phone APP, the rehabilitation plan, the training progress and real-time feedback are fed back, intelligent reminding is obtained, and through rehabilitation video or voice guidance, the patient can share experience, exchange rehabilitation experience and obtain psychological support and encouragement.

The invention relates to the technical field of medicine information management, in particular to a traceability method and system based on a medicine consumable traceability code. The method comprises the following steps: acquiring medicine purchasing information data; generating a unique code for the number of medicine purchasing information so as to generate a medicine warehousing traceability code; performing drug information association on the drug purchase information data according to the drug warehousing traceability code to generate a drug warehousing associated traceability code; storing the medicine warehousing associated traceability code in an information base to generate a medicine warehousing traceability code information base; performing scanning access mode division on the medicine warehousing traceability code, and generating a medicine dispensing scanning request mode and a medicine returning scanning request mode; and performing drug splitting tracing on the drug warehousing tracing code in a drug dispensing scanning request mode to generate drug splitting tracing data. According to the invention, through full-process closed-loop management, data association enhancement, intelligent scheduling optimization and drug return tracing improvement, the efficiency and precision of the drug consumable traceability code tracing method are improved.

The invention particularly relates to a data governance method and system based on a large model. According to the data governance method based on the large model, data are automatically collected, and the data are preliminarily cleaned and preprocessed; carrying out deep analysis, mining and prediction on the data by utilizing the large model, and carrying out data conversion and formatting according to business requirements; a data quality standard, a data security policy and a data management process are formulated and executed according to service requirements, so that the accuracy, integrity and security of data are ensured; the data quality and the data flow are monitored in real time, and if a data quality problem is found, the data quality problem is fed back to the large model so that the large model can solve the data quality problem in time. According to the data governance method and system based on the large model, intelligentization and automation of data governance are achieved, the burden of manual operation is relieved, the data governance efficiency is improved, the data security and compliance are optimized, intelligent decision support is achieved, and the data value mining capacity is improved.

The invention discloses a coal power multi-path transformation and new energy combination decision-making method under low-carbon transformation. The method comprises the following steps: firstly, constructing a system comprising first-level effect indexes such as environmental influence, economic benefit, energy safety and technical innovation and corresponding second-level indexes; then, alternative schemes of various coal power transformation technology and new energy project type combinations are generated; then quantitatively evaluating the effect index of each scheme, and calculating a comprehensive utility value by using multi-criterion decision analysis; identifying potential risk factors, and performing uncertainty analysis through Monte Carlo simulation; and finally, according to the low-carbon transformation target and policy evaluation scheme conformity, selecting a scheme which most conforms to the policy target, and continuously monitoring and adjusting. The coal-electricity multi-path transformation and new energy combination decision-making method under low-carbon transformation is beneficial to promoting energy low-carbon transformation, optimizing resource allocation, improving economic benefits, promoting technical innovation, enhancing risk management capability and ensuring that a project is consistent with policy orientation.

The invention discloses a fatty acid modified coronavirus antigen and application thereof, and belongs to the field of biological medicine. The fatty acid modified coronavirus antigen contains fatty acid modified N-terminal cysteine (Cys) and a coronavirus antigen, and can contain a connecting structural domain; the coronavirus antigen is a coronavirus spike protein (S protein) receptor binding domain (RBD). The fatty acid modified coronavirus S protein RBD can be self-polymerized into nanoparticles, and compared with the RBD which is not subjected to fatty acid modification, the antigen can induce faster and higher humoral immunity through injection immunity, can induce mucosal immunity and humoral immunity through respiratory tract atomization immunity, and is a candidate mucosal vaccine with potential medical value.

The invention discloses an electronic creditor's right certificate intelligent issuing method, which comprises the steps of S1, enhanced data collection and preprocessing: constructing an intelligent human-computer interaction interface, realizing efficient collection of specified data, and automatically analyzing uploaded document content; s2, deep data verification and intelligent analysis: analyzing the data by using a machine learning model to ensure accuracy, and verifying the logic consistency of the creditor and debt relationship; s3, self-adaptive creditor's right voucher generation: dynamically generating an electronic creditor's right voucher meeting legal requirements and industry standards by the system; s4, security enhancement and block chain evidence storage: endowing each electronic creditor's right certificate with a unique digital signature and a unique timestamp by adopting an encryption technology and a distributed account book mechanism; and S5, integrating and optimizing an automatic process, wherein the system design is compatible with various financial ecosystems. According to the invention, full-chain intellectualization from data acquisition and analysis to automatic voucher generation can be realized, and the issuing efficiency of the electronic creditor's right voucher is greatly improved.

The invention relates to the field of chronic disease early warning, and discloses a chronic disease early warning intervention system based on artificial intelligence, and the system comprises a data collection module which is used for collecting multi-modal data, and the multi-modal data comprises gene detection data, proteomics data, microbiomics data, environment data and social economic data; the pre-processing module is used for pre-processing the multi-modal data to obtain basic data, and the pre-processing comprises noise removal, abnormal value and missing value processing and targeted data cleaning and feature extraction operation on the data of different modals; and a conversion fusion module. Through cooperative operation of all the modules, a complete and automatic chronic disease early warning intervention process is formed, an organic whole is formed from data acquisition, risk assessment and intervention measure formulation and implementation, and the chronic disease risk whole process management and control are achieved, so that the chronic disease prevention and treatment efficiency and effect are improved.

The invention discloses an acute kidney injury risk early warning system, and relates to the technical field of clinical decision support systems. In order to solve the problems that in the prior art, due to the fact that a large amount of data preprocessing and model training need long-time data processing and model operation, the early warning opportunity is not accurate, the real-time performance is low, personalized early warning prompting cannot be carried out for patient groups, and early warning fatigue and early warning desensitization are likely to be caused. Through data preprocessing, model construction and risk analysis, real-time monitoring and accurate prediction of the AKI risk of a patient are realized, the early recognition rate is improved, the early warning decision unit generates specific early warning information according to risk scores and kidney function change rules and provides targeted treatment suggestions, and meanwhile, through an early warning threshold adjustment and approach matching module, the early warning decision unit can perform early warning on the AKI risk of the patient. The early warning strategy is optimized, the response speed of medical staff and the compliance of patients are improved, and the user interaction unit continuously optimizes the early warning system through a feedback mechanism.

The invention relates to the technical field of orthodontics, and discloses a processing system and a processing method for a bracket-free invisible orthodontic tooth socket, and the processing system comprises a data collection and integration module which is used for collecting and integrating multi-source data, comprising collection approaches and specific operation processes of oral three-dimensional scanning data, basic information of a patient, clinical examination records, correction scheme records and correction result evaluation; the data standardization and cleaning module is used for carrying out format unification and cleaning on the collected data; and the feature extraction and labeling module is used for extracting tooth form and tooth space relation features from the oral cavity three-dimensional scanning data and labeling the malocclusion and occlusion relation in the oral cavity. The invisible orthodontic tooth socket is manufactured by collecting a large amount of multi-dimensional data including oral three-dimensional scanning data, patient clinical information, orthodontic process records, result evaluation and the like, and the moving path of each tooth in each orthodontic stage and the magnitude and direction of required orthodontic force are accurately predicted.

The invention belongs to the technical field of biology, and particularly relates to a sweet protein composition as well as a preparation method and application thereof. The sweet protein composition comprises the following sweet proteins: at least one of Brazilian sweet protein, kiwi sweet protein, omethoate sweet protein, rhizoma curculiginis sweet protein, capparis masaikai sweet protein, miracle fruit element, petatin, thaumatin and agrocybe cylindracea sweet protein. The invention also provides a preparation method of the sweet protein composition, and the preparation method simplifies the purification process and significantly improves the purity and yield of the sweet protein. The sweet protein composition disclosed by the invention is suitable for various foods, beverages, medicines and health-care products, so that the taste of the medicines is improved, and the compliance of patients is improved. In addition, the sweet protein composition can also be used in weight-losing products, antioxidant supplements and health-care products for enhancing immunity, and oral care products such as toothpaste and mouth wash, and can provide pleasant sweetness and improve mouth feel.

The invention discloses an RPA-based full-automatic all-electricity invoice issuing method and system. The method comprises the following steps: constructing an RPA system: creating an RPA user, creating a business process, and defining a process rule; data acquisition and preprocessing: capturing basic transaction data, and performing data preprocessing on the captured data; invoicing and intelligent inspection: logging in a full-electricity invoice service platform, filling and submitting data information in an invoicing interface, and verifying various contents of an invoice; invoice circulation and signing determination: sending the issued full-electricity invoice to the user, and monitoring the invoice signing condition; and storage and filing management: uploading the issued all-electricity invoice to a management system. According to the invention, by introducing the RPA technology, the full-automatic processing of the full-electricity invoices from data acquisition and issuing to circulation and archiving is realized, the time consumption of manual operation is greatly reduced, and the invoice issuing efficiency is improved compared with the traditional manual or semi-automatic process.

The invention belongs to the technical field of cloud storage, and particularly relates to an enterprise service management cloud storage system which comprises a system initialization module, a distributed data storage module, a data encryption module, an authority control module, a multi-level cache module, a data backup and recovery module, a log monitoring module and a task scheduling and dynamic extension module. The distributed data storage module is responsible for dividing data in enterprise service management into a plurality of data blocks; the data encryption module is used for encrypting the enterprise service data stored in the cloud; the authority control module is responsible for managing the access authority of the user to the data; the multi-level cache module accelerates data access by configuring a local cache and a global cache; the data backup and recovery module is responsible for backing up the stored data regularly; the log monitoring module records various operation logs of the system; and the task scheduling and dynamic extension module is used for dynamically distributing calculation and storage resources according to the priority of the task and the utilization rate of the system resources.

The invention discloses a generative artificial intelligence auxiliary method and system for lower lumbago rehabilitation, and the implementation method comprises the following steps: S1, collecting health data of a patient in real time through a data collection module, and processing the health data; s2, the generative artificial intelligence auxiliary system converts the dialogue content between the patient and the doctor into a structured text record through an automatic voice recognition module and a natural language processing module, and the structured text record is integrated into an EHR system; s3, analyzing the health information of the patient by using the generative AI model, and generating a simplified medical language version; s4, generating a personalized rehabilitation scheme based on the health data; s5, the rehabilitation scheme is pushed to the patient through a user interface, and the generative artificial intelligence auxiliary system dynamically adjusts the rehabilitation scheme in real time according to feedback of the patient; and S6, continuously optimizing the generative AI model by continuously collecting patient feedback data. According to the invention, a personalized rehabilitation scheme can be automatically generated.

The invention discloses an Internet of Things service management system based on regional digital economy, and relates to the technical field of data processing. The Internet of Things service management system based on regional digital economy comprises a data minimization and anonymization module, an end-to-end encryption module, an access control and identity authentication module, a data security and auditing module and a security management and response module, and the data minimization and anonymization module is used for collecting personal sensitive information data; the end-to-end encryption module is used for encrypting a personal sensitive information data transmission process; the access control and identity authentication module is used for multi-factor authentication; the data security and audit module is used for protecting personal sensitive information data; and the security management and corresponding module is used for dynamically adjusting security policies and measures according to the privacy security state evaluation value. The problem that in the prior art, as the number of devices increases, more and more personal data are collected, and once sensitive data are integrated and analyzed, personal privacy may be exposed is solved.

The invention discloses a management method and system for guaranteeing the purchase quality of spare parts of a nuclear power plant, and relates to the technical field of equipment reliability and maintenance, and the method comprises the steps: collecting and coding the information of nuclear power spare parts; before the spare parts are purchased, the qualification of the supplier is verified; a demand list is automatically generated in the purchasing stage according to the coding information of the spare parts; matching suppliers meeting conditions in a supplier database according to the content of the demand order, and generating a purchase order; the unique code of the safe and important spare part is collected, and an RFID label or a two-dimensional code label is pasted on the spare part; spare part codes and supplier information are checked by scanning RFID or two-dimensional code labels, it is ensured that the spare part information is consistent with a purchase order, and then the spare part information is put in storage. According to the invention, spare part purchasing quality process control is realized, technical clarification is greatly reduced, one-code multi-object problems are reduced, purchasing efficiency is improved, and counterfeiting is prevented, so that quality of safe and important spare parts is ensured, nuclear power plant equipment reliability is improved, and safe and stable operation of a unit is ensured.

The invention relates to the technical field of medical treatment, and discloses an intelligent subject evaluation method based on multi-dimensional data, which comprises the following steps: acquiring the multi-dimensional data corresponding to a subject, inputting the multi-dimensional data into a pre-trained evaluation model, and acquiring an analysis report of the subject participating in clinical research, the multi-dimensional data comprises clinical symptoms, traditional Chinese and western medicine diagnosis, medication information and social background of the subject, and the analysis report comprises accuracy, compliance and risk; based on the analysis report, determining a corresponding group-entering suggestion and a treatment research scheme for each subject, the treatment research scheme including drug selection, dose adjustment and a follow-up plan; in the clinical research process, the latest research data are continuously obtained, and the analysis report and the treatment research scheme of the subject are adjusted based on the latest research data. The quality and effectiveness of clinical research can be improved.

The invention belongs to the technical field of biological materials, and particularly discloses a blood vessel biological patch and preparation thereof, the blood vessel biological patch has the maximum tensile elongation of 20.1-35.1%, the elastic deformation rate of 15.1-29.4%, the value of the elastic deformation rate accounting for the maximum tensile elongation is 54-90%, and the bursting strength is 38-55N. The blood vessel biological patch provided by the invention can effectively reduce bleeding at the suture after carotid endarterectomy and prevent the problem of unstable performance of the biological patch.

The invention relates to the technical field of data encryption, in particular to an intelligent medical information data encryption method and system and a medium. The method comprises the following steps: acquiring medical information data by using an electronic health recording system; initial AES-256 encryption is conducted on the collected medical information data, the encrypted medical information data are stored in a database, a medical information encryption database is obtained, and the medical information encryption database comprises at least one medical information record; and carrying out expiration timestamp distribution on each medical information record to obtain a medical information encryption expiration timestamp. According to the method, efficient and safe management of medical information data is realized through dynamic management of encryption strength, expiration time check and intelligent contract optimization, so that the security of the data is improved, the burden of the system is reduced, the compliance and flexibility of medical data storage and access are enhanced, and the overall performance of users and the system is improved.

The invention discloses a data security compliance evaluation and identification method and system, and relates to the technical field of data security compliance evaluation and identification, and the method comprises the steps: collecting regulation text data through an API interface, and carrying out the preprocessing of the regulation text data through a natural language processing library NLTK, and obtaining formatted regulation text data; mapping each word in the formatted law and regulation text data into a fixed-length vector by adopting a pre-calculation word embedding method, and generating a digital vector; marking important terms in the digital vector by adopting a named entity recognition NER method to obtain a key concept text; establishing an evaluation model based on a machine learning algorithm, inputting the digital vector into the evaluation model, calculating and outputting an evaluation value by adopting a weighted average method, setting an evaluation threshold value, comparing the evaluation threshold value with the evaluation value, judging whether the digital vector is compliant or not, and obtaining an evaluation result; and constructing a recognition model based on an anomaly detection algorithm, and inputting the key concept text into the recognition model.

The utility model relates to the technical field of light feeding devices, in particular to an eye-closed three-dimensional light feeding LED device, which is characterized in that a pupil LED chip group comprises a red light chip and a near-infrared light chip with the wavelength range of 625nm to 960nm; a pupil LED chip set, an eyelash LED chip set and a meibomian gland LED chip set are fixedly installed on the pupil aluminum substrate, and forced eye closing distance control hair is arranged on the pupil aluminum substrate. A lens aluminum substrate and an eyebrow acupoint aluminum substrate are mounted on the lens seat; the system further comprises an integrated control circuit. By using the red light chip, the optical power density comparable to that of laser and the effective irradiation area larger than that of the laser can be obtained, and the alignment precision of a light source to acupuncture points is reduced; by utilizing the blood activating function of dark red and near-infrared light, myopia, eyebrow thickening and eyelash thickening can be prevented and controlled; health care can be carried out on meibomian glands and a suspension tough system, and light stimulation can be carried out on eye protection acupuncture points; all-directional three-dimensional light feeding can be realized anytime and anywhere; the safety values under various limit conditions refer to three kinds of sunlight.

The invention discloses a risk assessment method for enterprise cross-domain data. The method comprises the following steps: collecting original assessment data of an enterprise for data exchange and sharing among different departments; preprocessing the collected original evaluation data, wherein the preprocessing comprises the steps of carrying out standardization processing on numerical data and carrying out fuzzification processing on text description data; constructing a risk assessment model based on a Bayesian network, and determining a dependency relationship and a conditional probability between risk factors by introducing expert knowledge and historical data; calculating the posterior probability of each risk factor through a Bayesian network; an expert evaluation method is adopted to allocate a weight for each risk evaluation index to carry out risk-based scoring on each risk factor; and calculating a comprehensive risk score of the enterprise cross-domain data through a comprehensive risk scoring formula. According to the method, an enterprise can be helped to accurately evaluate and manage risks in a complex data environment, and the data security and compliance are improved.

The invention discloses a space neglect rehabilitation training system based on artificial intelligence. The system comprises a space neglect evaluation module used for evaluating the space neglect condition of a patient through a space neglect evaluation program; the rehabilitation program setting module is used for setting a rehabilitation program of the mobile wearable equipment by utilizing a rehabilitation program setting model according to the related data of the patient; the wearable equipment execution training command module is used for executing a corresponding rehabilitation task by the mobile wearable equipment according to the rehabilitation program set in the rehabilitation program setting module and recording the completion condition of the rehabilitation task; and the terminal collection feedback module is used for reading the training data of the patient, evaluating and judging the training compliance of the patient by utilizing the training data of the patient and constructing a training effect analysis model, and generating an adjustment strategy of a rehabilitation training scheme. Through the system provided by the invention, the training compliance and effect of the patient can be comprehensively and objectively evaluated, and the quality and efficiency of rehabilitation treatment are improved.

The invention relates to the technical field of visual health management, in particular to a ciliary muscle adjustment training system and method based on eye movement tracking, and the method comprises the steps: collecting eye movement data of a fixation point track, an adjustment amplitude change rate and pupil response time in real time, and combining personalized parameters such as the age of a user, diopter and a training target; inputting a ciliary muscle training dynamic planning algorithm module, dynamically generating a stage scheme containing a training action type, a single-group duration, a stimulation interval and a focal length adjustment strategy, and adaptively adjusting the strategy according to real-time adjustment stability and a historical ability curve; through multi-dimensional matching analysis of a pre-stored standard eye movement template, a training specification score is calculated from the track goodness of fit, speed uniformity, amplitude standard-reaching rate and binocular coordination, visual fatigue parameters are obtained based on continuous training duration, pupil fluctuation and retina reflex change, a scoring result is dynamically corrected, and a visual fatigue evaluation result is obtained. Personalized, self-adaptive and quantitative safety control of the training process is realized.

The invention provides a preparation composition of a glucagon-like peptide-1 receptor agonist for nasal mucosa administration, and particularly relates to the technical field of biological medicine materials. The preparation composition mainly comprises a glucagon-like peptide-1 receptor stimulant, alkyl glycoside and phospholipid, wherein the ratio of the glucagon-like peptide-1 receptor stimulant to the alkyl glycoside to the phospholipid is (0.25-17.5): (0.25-10): (0.1-10) by mass. The active pharmaceutical ingredients in the preparation composition provided by the invention are delivered through nasal mucosa, directly enter blood circulation from an absorption part, can take effect quickly, have higher bioavailability, and improve the compliance of patients.

The invention discloses a Gegen Qinlian decoction vesicle-like nanoparticle as well as an extraction method and application thereof, and belongs to the technical field of biological medicines. The method comprises the following steps: preparing a radix puerariae qinlian decoction stock solution; placing at 4-8 DEG C for 12-15 hours to obtain a gelatinous substance; carrying out low-speed centrifugation at 4-8 DEG C, and taking supernate, so as to obtain crude extract of the vesicle-like nanoparticles of the radix puerariae, radix scutellariae and rhizoma coptidis decoction; carrying out ultracentrifugation at 4-8 DEG C, discarding the supernatant, and carrying out PBS resuspension precipitation to obtain a crude product of the vesicle-like nano-particles of the Gegen Qinlian decoction; and centrifuging 16000g at the temperature of 4-8 DEG C for 10-15 minutes, taking supernate, and filtering by using a 0.22 mu m filter membrane, so as to obtain the vesicle-like nanoparticles of the Gegen Qinlian decoction. According to the Gegen Qinlian decoction vesicle-like nanoparticles as well as the extraction method and the application thereof, the bioavailability and the targeting property of effective components in the Gegen Qinlian decoction are remarkably improved through a nanocrystallization technology, the concentration of the medicine at the ulcerative colitis part is enhanced, and the treatment effect is effectively improved.

The invention provides a balloon catheter suitable for long vasculopathy, and relates to the technical field of medical instruments. The first balloon is arranged at the far end of the catheter body; the diameter of the near end of the first balloon is larger than that of the far end of the first balloon. A through inner cavity is formed in the middle of the catheter body, and a communicating channel communicating the first balloon with the inner cavity is formed in the side wall of the catheter body. By arranging the first balloon and the second balloon, the first balloon extrudes the second balloon after expanding, so that a contrast agent in the second balloon is gradually extruded out, the second balloon deforms, and the deformed second balloon is better attached to the narrow part of a blood vessel and can better adapt to the change of the inner diameter of a channel at a longer blood vessel.

The present application proposes a standard-based data asset governance method, including extracting link descriptions and link IDs of a data governance process; accessing a standard library that the data asset process depends on to obtain standard file descriptions and standard file IDs that constrain the data governance process; performing attention analysis on link descriptions and standard file representations to obtain a standard compliance matching graph; constructing a standard metadata model based on the standard compliance matching graph, and encoding the standard metadata model to obtain a standard mapping table to construct a standard data governance rule engine; assigning roles to a data-based governance organizational structure, and establishing a workflow control model between the assigned roles and link descriptions; establishing an object collaborative mapping framework between the workflow control model and the standard data governance rule engine to perform standard data asset governance tasks based on the object collaborative mapping framework.

According to the multi-modal intelligent question answering method and device, the storage medium and the computer equipment, when the query question is received, the target query text of the query question is extracted to avoid input carrier limitation of the query question, then the target query text is vectorized into the target text vector, and the query question is queried according to the target text vector. The target text block is obtained based on the target query text and the target text vector, so that the retrieval accuracy is improved; and then optimizing the target text block by adopting the target text optimization model and outputting a high-accuracy target answer. If the target answer contains the picture address, a picture request is initiated to the server after a request address corresponding to the picture address is generated, and the server performs security verification on the request address and returns picture content corresponding to the picture address after the request address passes the security verification, so that the data security is improved; and finally, replacing the picture address in the target answer with the picture content, and displaying the final target answer to the user through a multi-modal mode of the text and the picture, so that the intuition and the accuracy are improved.