151 results about "Information evaluation" patented technology

The invention belongs to the technical field of information, and relates to a multi-level dynamic intelligent automatic data processing and information evaluation method and system. The method comprises the steps that a database environment operation data set is constructed, targeted training and fine adjustment are conducted on a large language model in combination with reinforcement learning, and full-automatic data analysis, query and information extraction of multiple tables in a database are achieved; a multi-level agent interaction and cooperation framework is established, a scheduling agent is responsible for global decision making and strategy planning, an operation agent is responsible for execution of specific tasks, and the scheduling agent and the operation agent share information and coordinate the tasks to form a highly cooperative whole; and establishing a cyclic supervision and error correction mechanism, scheduling the intelligent agent to learn a normative workflow example of the target working environment and track the state of the operation intelligent agent in real time, identifying the behavior of the operation intelligent agent deviating from a predetermined path, and taking corrective measures. According to the method, high efficiency, intelligence and automation of data processing are realized, and the method has remarkable practical value and innovative significance.

A data collection unit (11) collects information related to an object and sets the information as collected data (101). A data normalization unit (12) adds, as an input type, the type of data to the collected data (101) collected by the data collection unit (11), and thereby generates training data (102). A training unit (13) trains a machine learning model (103), which is a large-scale language model, on the basis of the training data (102) generated by the data normalization unit (12). By using the trained machine learning model (103) and a portion of visualization data that includes configuration information, state information, and evaluation information of the object and information indicating relationships of the object with other related objects, an inference unit (14) infers the information in the visualization data other than said portion. A correction unit (15) corrects the information in the visualization data inferred by the inference unit (14), on the basis of the collected data (101).

The invention relates to a bid invitation information feedback comparison system based on big data, and relates to the technical field of big data, and the system comprises an information acquisition module, an information processing module, an information extraction module, an information comparison module, an information evaluation module, a ranking calculation module and a decision generation module. The technical key points are as follows: bid invitation and bidding document information is collected, and a document database is constructed; and extracting qualification evaluation feature words by using a natural language processing technology, and comparing the qualification evaluation feature words with preset qualification demand information to generate a qualification bid evaluation report. In addition, the method further comprises the steps of evaluating the price rationality of the bidding party quotation information, and generating a price evaluation report according to the price rationality. And finally, calculating the ranking of the bidding parties according to each bid evaluation report, generating decision support information, and marking the bidding party with the top ranking as a recommended bidding party. Through comprehensive qualification and price evaluation, a simple, efficient and practical solution is provided for small and medium-sized enterprises.

The invention provides an AI-based talent whole-process management method and device, electronic equipment and a medium, and the method comprises the steps: obtaining a recruitment application submitted by a recruiter, building a recruitment post after the recruitment application passes the approval, and generating the post responsibility information of the recruitment post based on a first sub-module of an AI model; obtaining resume information of the applicant, executing a resume information evaluation task based on a second sub-module of the AI model, and calculating a matching degree score between the resume information and the recruitment post; an interview invitation is sent to the applicant based on the matching degree score, an interview evaluation task is executed through a third sub-module of the AI model, the applicant receiving the interview invitation is interviewed, and an evaluation result of the interviewed applicant is obtained; and determining candidates based on the evaluation result, and sending a review notification or an in-job invitation notification to the candidates. According to the invention, the recruitment process is optimized, and the recruitment quality is improved.

The invention relates to the technical field of information fusion, in particular to a power equipment state information fusion system and method. The method comprises the following steps: obtaining time sequence signal data and infrared thermal image data, and constructing a power equipment heterogeneous fusion data set; acquiring power equipment position and power equipment environment data, performing multi-layer cross-mode data coupling in combination with the power equipment heterogeneous fusion data set, and constructing a power equipment information evaluation model based on the multi-layer cross-mode data coupling; therefore, through multi-source data fusion and cross-level evaluation model construction, the problems of a traditional power equipment monitoring system in the aspects of information island and prediction accuracy are solved, and the health management capability and fault early warning efficiency of power equipment are improved.

The invention belongs to the field of artificial intelligence and knowledge graph application, and relates to an intent-driven large model knowledge graph intelligent question and answer method and an intelligent agent. The method comprises the steps of receiving a question input by a user, and identifying a potential intention of the user; according to the identified intention and the information stored in the shared memory, selecting a proper tool from a tool only based on a large language model, a tool based on semantic analysis, a tool based on sub-graph retrieval and a general tool for reasoning; new information generated by the tool is updated into the shared memory; and in each iteration, the large language model evaluates the current reasoning state according to the information stored in the shared memory, and triggers a tool with a corresponding intention to perform supplementary reasoning according to the current reasoning state until enough information is collected to draw a conclusion or a preset upper limit of the number of iterations is reached. The method can improve the reasoning efficiency and accuracy, can be applied to complex question answering in various fields, and provides high-quality question answering service for users.

The invention discloses an occupational information evaluation method based on rule judgment and a large language model, and belongs to the technical field of information processing, and the method comprises the following steps: S1, obtaining a multi-modal document uploaded by a user, converting the multi-modal document into a Markdown format, and completing a shunting operation and a converging operation; s2, extracting a named entity of the multi-modal document after the confluence operation, and constructing a knowledge graph; s3, obtaining query content, and matching most relevant regulation content by using the knowledge graph; s4, generating specific improvement suggestions by utilizing the rule model according to the most relevant regulation content; and S5, adjusting the specific improvement suggestions by using a large language model to obtain a final evaluation result. Through the OCR technology, regular expression analysis and context-associated picture analysis, unified structured processing of texts, tables and pictures is achieved, and the problem that unstructured data are difficult to integrate in a traditional method is effectively solved.

The invention discloses an insurance evaluation large model training method and device, equipment and a storage medium, and relates to the technical field of data processing. Comprising the steps of performing data compliance processing on medical training data and financial training data provided by participants participating in model training through a federal learning architecture in a preset distributed data management component to obtain compliance data; reading compliance data from a preset distributed data management component based on a preset data fusion engine, and performing fusion processing to obtain cross-domain fusion data; obtaining cross-domain fusion data by using a preset large model joint training framework, and generating a target model training task based on the model training capability corresponding to each participant; and training the to-be-trained model according to the target model training task and the cross-domain fusion data to obtain a target insurance evaluation large model so as to perform medical insurance information evaluation based on the target insurance evaluation large model. In this way, efficient retrieval and compliance sharing of medical and financial cross-domain data resources can be achieved.

The invention relates to the field of mine geological environment monitoring and evaluation, in particular to an intelligent mine geological environment information evaluation method based on a knowledge graph. The method comprises the steps that mine geological environment data are collected and preprocessed, a knowledge graph is constructed based on the preprocessed mine geological environment data, and embedded vectors of nodes in the knowledge graph are obtained; calculating space-time similarity among the nodes based on the embedded vectors of the nodes; iteratively optimizing the embedded vectors of the nodes by adopting a graph neural network to obtain final embedded vectors of the nodes; a self-adaptive edge weight updating mechanism is introduced, and edge weights among the nodes are dynamically adjusted to obtain final edge weights among the nodes; and comprehensively evaluating the mine geological environment based on the final embedding vector of the nodes and the final edge weight between the nodes. The problems that a traditional monitoring and analysis method neglects spatial and temporal characteristics of a mine geological environment, and accurate prediction and risk early warning are difficult to carry out are solved; and real-time self-adaptive updating cannot be carried out, so that the timeliness of an evaluation result is poor.

The invention relates to the technical field of medical signal processing, and discloses an anesthesia depth multi-level classification information assessment method and system, and the method comprises the steps: collecting an electroencephalogram signal, and carrying out the preprocessing operation of the electroencephalogram signal, and obtaining signals of five frequency bands; global field power is calculated for all electroencephalogram signals of each frequency band, and a peak topographic map is identified; performing clustering analysis to extract a micro-state template, and matching and reconstructing a micro-state time sequence; and establishing a feature screening and classification identification model, inputting each frequency band signal into the feature screening and classification identification model, screening the extracted micro-state features, carrying out multi-level classification on the anesthesia depth, and finally outputting an anesthesia depth evaluation result. The system comprises an electroencephalogram collecting and processing module, a clustering reconstruction module and an anesthesia depth evaluation module. According to the method, the preprocessed electroencephalogram signals are decomposed through Hilbert-Huang transform, and anesthesia depth evaluation is achieved.

The invention discloses a motor multi-parameter identification method based on sampling noise excitation and bias compensation, and the method comprises the steps: firstly obtaining the voltage and sampling current of a motor, and enabling the sampling current to comprise sampling noise; then constructing an information evaluation index, and adjusting a proportional parameter of a current controller to improve the identification information amount; then, shaft voltage feed-forward compensation is constructed to suppress electromagnetic torque pulsation; recursion is carried out by adopting a least square method based on the discrete linear parameterization model to obtain a parameter initial value and a covariance matrix; secondly, estimating offset-containing parameters on line, and calculating a sampling noise variance by using an estimated residual error; and finally, obtaining unbiased parameter estimation according to bias compensation iteration updating so as to output online estimation values of stator resistance, direct-axis inductance Ld, quadrature-axis inductance Lq and permanent magnet flux linkage.

The invention provides a prompt information evaluation method and device, electronic equipment, a medium and a program product, and can be applied to the technical field of artificial intelligence. The method comprises the steps that a pre-constructed query statement test data set is obtained, the query statement test data set at least comprises a plurality of error query statements, and each error query statement is used for triggering a target database to generate error prompt information in the execution process; inputting the error query statement into the target database, obtaining return information of the target database, and generating error prompt information based on the return information; based on the error prompt information, utilizing a large language model to obtain at least one corresponding correction query statement; and verifying the corrected query statement in the target database, and evaluating the quality of the error prompt information based on a verification result.

1. Name of this design product: Graphical user interface for a central control visualization platform for electronic equipment in a civil aviation cabin. 2. Purpose of this design product: an electronic device. 3. The key design point of this design product lies in the graphical user interface on the screen. 4. The picture or photo that best illustrates the key points of the design: main view. 5. The physical product is of conventional design and other views are omitted. 6.Purpose of the graphical user interface: used to summarize and update data display of civil aviation cabin information. The interface displayed in the main view is the graphical user interface of this software. The middle area of ​​the main view shows the flight cabin data summary, and the left and right sides show data indicators. The left side shows the cabin central control visualization platform, cabin service management and power consumption trend respectively. The right side shows the cabin response information evaluation, the real-time status of temperature and humidity in each cabin area and the cabin service demand data statistics. The lower middle area shows the real-time video inside or outside the cabin. In the main view, click on the "In-cabin response information evaluation" text area, and a pop-up window will display data indicators such as in-cabin service evaluation and in-cabin response times.

The invention discloses a reverse guidance type intelligent interaction method and system for realizing dynamic information assessment. The system comprises an information sufficiency assessor, an information sufficiency assessment device and a dynamic information assessment device, wherein the information sufficiency assessor is used for dynamically and quantitatively assessing and identifying key information gaps on the basis of an information entropy theory; the reverse questioning strategy generator is used for generating an optimal reverse guidance questioning sequence for supplementing a key information gap based on a Markov decision process model; the hierarchical problem decomposition engine is used for recursively decomposing a complex problem into a plurality of sub-problems by adopting a semantic tree decomposition technology, and fusing solution results of the sub-problems by utilizing an evidence theory fusion mechanism to form a problem solution; the personalized solution synthesizer is used for analyzing the cognitive level, learning style and attention characteristics of the user portrait, performing matching optimization on a problem solution and the user portrait, and calculating and measuring the semantic matching degree of the problem solution and the user portrait; and applying reinforcement learning to continuously optimize an output strategy according to user feedback to generate a personalized solution.

The invention relates to the technical field of medicine, and provides a medicine clinical value evaluation method and system, electronic equipment and a storage medium, and the system comprises a medicine information collection module which is used for obtaining first information of a to-be-evaluated target medicine; the evaluation standard construction module is used for setting an evaluation standard based on a preset evaluation requirement; the standard quantitative assignment module is used for performing weight assignment on the evaluation standard; the evaluation evidence integration module is used for acquiring second information of the target drug based on the evaluation standard set by the evaluation standard construction module and the first information; and the drug value evaluation module is used for evaluating the clinical value of the target drug based on the second information of the target drug by applying an evaluation standard. The method and the device are used for overcoming the defects of dimensionality stiffness, quantization distortion, evidence dispersion and decision lag during evaluation of the clinical value of the medicine in related technologies. The method and the device can be used for realizing scientific evaluation, dynamic management and scenarized decision of the clinical value of the medicine.

The invention discloses an enterprise credit information assessment system and method, and the system comprises a data collection module, a data screening module, a text recognition module and a risk assessment module: the data collection module is used for collecting enterprise public information corresponding to a to-be-assessed enterprise; the data screening module is used for cleaning and screening the enterprise public information according to the consistency among various information in the enterprise public information to obtain to-be-evaluated information; the text recognition module is used for performing text recognition on the to-be-assessed information and extracting multiple pieces of target information corresponding to the to-be-assessed enterprise in the to-be-assessed information; and the risk assessment module is used for analyzing and predicting each piece of target information based on a preset identification model, determining the credit risk of the to-be-assessed enterprise, generating an enterprise credit information report based on the credit risk, and completing credit information assessment of the to-be-assessed enterprise. According to the invention, accurate and efficient evaluation of enterprise credit information is realized.

The invention discloses a highway information evaluation method based on data management, and relates to the technical field of highway evaluation, and the method comprises the evaluation steps: S1, collecting highway traffic flow data, pavement state data and local meteorological data, and carrying out the preprocessing of the collected data; s2, extracting a correlation calculation characteristic value from the preprocessed data, synchronizing the processed data according to a time dimension, and enabling the collected data to correspond to each other; and S3, calculating a pavement damage rate, a traffic jam rate and a meteorological influence rate based on the data. According to the invention, the evaluation score is obtained by comprehensively considering each factor, a scientific basis is provided for the management decision, the grading and maintenance decision can determine the condition grade, make the maintenance strategy according to the grade, realize reasonable resource allocation, improve the overall operation and maintenance management level of the expressway, and avoid the problem of dependence on single data evaluation. The processing flow is effectively improved, and accurate evaluation and analysis are carried out.

The invention discloses a method for positioning and detecting key parts of hatching eggs. The method comprises the following steps: acquiring transmission images in hatching eggs of different days through a hatching egg image acquisition device, and training and establishing a hatching egg physiological state judgment model and a hatching egg key part segmentation model; the discrimination model outputs a transmission image of the fertilized egg to be positioned and detected, the key part is identified after the transmission image is processed by the segmentation model, then the optimal coordinate point extracted by the allantoic fluid is positioned by adopting an image processing method, and the allantoic fluid is extracted to realize the detection of the hatching egg. According to the method, a dual model of hatching egg development evaluation and key part identification is established, interference of human subjective factors is weakened, and detection and classification errors are reduced; the allantoic fluid coordinate positioning method reduces the risk of puncturing and damaging the embryo and improves the allantoic fluid extraction success rate; according to the invention, rapid and accurate hatching egg information evaluation and male and female chick embryo difference characteristic detection can be provided according to hatching application requirements.

The invention belongs to the technical field of false information spreading and screening, and particularly discloses and provides a network news false information spreading and screening method, which comprises the following steps: screening key evaluation dimensions based on historical data, determining weights, generating evaluation rules, and determining the weight of each evaluation rule; determining a conventional or emergency monitoring mode according to the amplification of the forwarding quantity of the information to be screened and the number of matched words in a preset keyword library, identifying an initial publishing source through a propagation path, evaluating source authority, content consistency and propagation abnormality in the conventional mode, and outputting comprehensive credibility; in the emergency mode, the emergency credibility is directionally and rapidly evaluated and output, and finally, the credibility is matched with the early warning interval to obtain an early warning level; according to the method, the source authority is assessed based on the source information, the content consistency is judged through the text content, the propagation abnormality is assessed through the propagation data, the comprehensive credibility is output in combination with the assessment dimension rule, and multi-dimensional collaborative assessment of the source, the content and the propagation is achieved.

The invention provides an automatic software test method and system, a storage medium and equipment, and the method comprises the steps: obtaining a target code, extracting related information and test requirements, and generating a test case according to the target code and the test requirements through a trained large model; in response to the code change information, evaluating the influence range of code change on the test case, performing static analysis, determining the change of a code structure, performing dynamic analysis, and determining the change of a code execution path; according to the evaluation result of the influence range of the code change on the test case, determining a test case automatic adjustment strategy, running the adjusted test case, obtaining log data in the running process, extracting error information in the log data, performing code mapping on the error information, and determining an error position. According to the method, a large model technology is utilized, and the processes of automatic generation, intelligent adjustment, automatic result analysis, accurate problem positioning and the like of the test case are optimized, so that the efficiency and the accuracy of software testing are remarkably improved.

The invention relates to the field of limb exercise rehabilitation, in particular to an evaluation and training method for limb rehabilitation exercise of old people, and the method comprises a rehabilitation data collection module, an evaluation module and a training plan making module, the rehabilitation data collection module is used for collecting real-time rehabilitation information when the old people perform rehabilitation exercise in a current rehabilitation training period; the training plan making module is used for collecting rehabilitation test information of the old in a current rehabilitation exercise test, the evaluation module obtains and outputs a basic evaluation value, an endurance evaluation value and a rehabilitation effect evaluation value according to real-time rehabilitation information, the rehabilitation test information and historical evaluation data, and the training plan making module is used for automatically making a training method of a next rehabilitation training period. According to the method, the joint motion ability and pain feeling of the elderly patient are comprehensively considered, the exercise endurance related factors are introduced, the rehabilitation condition of the elderly patient is evaluated more comprehensively, the rehabilitation effect is dynamically monitored later, a scientific basis is provided for adjusting a rehabilitation training plan, and comprehensive, dynamic and personalized rehabilitation evaluation and training are achieved.

The invention relates to a room graph model consistency comparison method and device of an engineering drawing. Comprising the steps of extracting first bounding box information and first room label information of a room based on a PDF format drawing, and extracting second bounding box information and second room label information of the room based on an IFC model file; and aligning the first bounding box information and the second bounding box information in the same coordinate system, and evaluating the consistency of the room information of the PDF format drawing and the IFC model file based on a coordinate alignment result, the first and second bounding box information and the first and second room label information to obtain a drawing-model consistency evaluation result. Therefore, by identifying and comparing the room information in the PDF drawing and the corresponding room information data in the IFC model, the problems that in the prior art, the format of the processed drawing is single, and the review result is incomplete are solved, and effective review of consistency of the design drawing and the building model in spatial layout and function is achieved.

The invention relates to the technical field of enterprise information management, in particular to an enterprise multi-dimensional information management system based on artificial intelligence. Comprising a data acquisition unit used for acquiring enterprise internal data and public data; the data preprocessing unit is used for performing data cleaning on the data acquired by the data acquisition unit and storing the data in the data storage unit; the information evaluation unit is used for extracting the data in the data storage unit, calculating industry trend parameters, market demand parameters and policy orientation indexes and calculating information evaluation parameters M and is used for assisting enterprises to predict and judge market development changes; the information early warning unit is used for evaluating whether the enterprise internal data accords with a preset threshold value or not; and the display unit is used for displaying the data information, the information early warning parameter M and the early warning information in the data storage unit. According to the invention, effective management and analysis of information are realized, enterprise decision making and operation are assisted through identification and mining of enterprise internal information and public information, and management of enterprise information resources is optimized.

An assistance control system (100) containing a map database (4) storing map information and executing an assistance control to cause a moving object to move to a destination based on map information, the assistance control system comprising an electronic control unit configured to: generate or update the map information based on an input from a sensor attached to the moving object, to identify a large number of route candidates to the destination, to assess the security of the map information for each location or section and to calculate a map information assessment value, to evaluate the accuracy of the assistance control on the identified route candidates based on the calculated map information evaluation value, to set a priority for a route candidate with a lower rating among the route candidates higher than the priorities of other route candidates, to present a route candidate with the highest priority among the route candidates to an occupant of the moving object, or to steer the moving object along the route candidate with the highest priority, and update the map information evaluation value as a result of the movement of the moving object along the route candidate with the highest priority, and lower the priority of the route candidate with the highest priority based on an amount of change in the map information evaluation value within a predetermined time, wherein, when the number of times the moving object has moved along the route candidate having the highest priority is equal to or greater than a predetermined number of times, the electronic control unit may be configured to determine whether the amount of change between the map information evaluation value before the movement of the moving object and the map information evaluation value after the movement of the moving object is equal to or less than a first predetermined amount, and lower the priority of the route candidate having the highest priority when the electronic control unit determines that the amount of change is equal to or less than the first predetermined amount.

This application discloses a health detection method and system for new energy electric vehicles, relating to the field of big data technology, including: S101, collecting and storing the driver's biometrics and uploading it to a cloud platform; S102, storing and analyzing health data on the cloud platform; S103, viewing health data and health status; Step S102 is implemented in the following way: S201, determining the driver's health status based on the vital sign data; S202, establishing a health feature database, comparing the time series data of the cloud platform with the health feature database, and identifying the current health status of the driver; the health feature database is built into a hierarchical tree based on the time series data, and the hierarchical tree generates cluster superposition centers based on different difference points; the information evaluation rate and similarity rate are obtained based on the cluster superposition centers; it can effectively help drivers manage their own health status and effectively assist driving.

The present disclosure provides a sample generation method, a machine learning model training method, an information evaluation method, an apparatus, a device, a storage medium and a program product, relates to the technical field of computer and data processing, and particularly relates to the technical field of artificial intelligence, machine learning, big data, data mining and the like. The specific implementation scheme is as follows: for any one content publishing subject, determining target information according to the publishing content of the content publishing subject; determining a label for each content publishing subject according to the target information; and for any one content publishing subject, generating a subject sample according to the label.

The invention belongs to the technical field of new energy vehicles, and particularly relates to a hybrid vehicle approximate optimal energy management strategy integrating prediction and control, and the strategy specifically comprises the following steps: (1) constructing a global prediction domain, predicting a global speed curve through employing a bidirectional long-short-term memory network based on traffic data, and obtaining a global speed curve; obtaining a global approximate optimal reference state-of-charge sequence through a dynamic programming algorithm; (2) constructing a mesoscopic coordination domain, performing mesoscale speed prediction by adopting a method of fusing an encoder and a bidirectional long-short-term memory network, and solving a multi-scale information evaluation factor online and performing dynamic correction in combination with a grey wolf optimization algorithm; and (3) constructing a real-time control domain, introducing the evaluation factor to construct a multi-target optimal real-time control framework, and realizing instantaneous optimal mode decision and power distribution. According to the method, the economy, the smoothness and the NVH performance are comprehensively considered, global reference and real-time control are effectively decoupled, and the adaptability of the vehicle to a complex dynamic driving scene and the fuel economy of the whole vehicle are remarkably improved.

The invention relates to the technical field of computers, in particular to a vehicle position information verification method and device, electronic equipment and a medium, and aims to improve the accuracy of position information verification. The method comprises the following steps: acquiring point cloud data periodically acquired by taking a vehicle as a reference in a preset range, matching the acquired target point cloud data with a point cloud map after the point cloud data is acquired each time, and acquiring target position information and an information evaluation value of the vehicle based on a matching result; when the information evaluation value belongs to a preset evaluation interval, obtaining position change information of the vehicle based on the target position information and historical position information of the vehicle; and obtaining a verification result of the target position information based on the position change information and the reference change information. As the reference change information provides reference position changes when the point cloud data are collected twice, whether the target position information is accurate or not can be judged in an auxiliary mode by comparing the reference change information with the position change information, and the accuracy of position information verification is improved.

The invention discloses an information evaluation method and device, electronic equipment, a storage medium and a program product. The specific implementation scheme comprises the steps of determining to-be-evaluated information; determining a multi-kernel convolution model comprising multiple groups of dynamic convolution kernels; extracting features of the to-be-evaluated information based on the multi-kernel convolution model, and generating a length sensing text vector corresponding to the to-be-evaluated information; and based on the first length perception text vector and the second length perception text vector, determining a recruitment score corresponding to the to-be-evaluated information. The to-be-evaluated information is analyzed through the multi-kernel convolution model comprising multiple groups of dynamic convolution kernels, so that truncation of the to-be-evaluated information is avoided, and information loss in the evaluation process is reduced. According to the method, the length sensing text vector of the to-be-evaluated information is obtained, and the recruitment score is obtained based on the length sensing text vector, so that the rationality of the recruitment information in the to-be-evaluated information is evaluated, and the rationality of the recruitment information is ensured.

The present disclosure provides an information query method, device, equipment, storage medium and program product, relates to the technical field of data processing and computer, and particularly relates to the technical field of big data and intelligent search. The specific implementation scheme of the information query method is as follows: determining at least one candidate key information matched with the query information according to the query information; determining a first evaluation value for evaluating the candidate key information according to a key information evaluation parameter; determining at least one target key information from the at least one candidate key information according to the first evaluation value; and determining target content information according to the at least one target key information.