52results about How to "Efficient matching" patented technology

The invention discloses an intelligent visualization and text association method for a multi-modal knowledge graph, and relates to the technical field of information processing. According to the intelligent visualization and text association method for the multi-modal knowledge graph, multi-modal data in an internal database of an enterprise is obtained, and a multi-modal feature vector is generated by using a data preprocessing and feature extraction technology; the feature vectors are mapped to a unified vector space through a cross-modal embedding algorithm, semantic alignment, association and fusion among multi-modal data are realized, and a complete multi-modal knowledge graph is constructed. Through bidirectional association and multi-modal joint query, the information acquisition efficiency is improved, and visual display of the knowledge graph is realized by using the graph neural network. Meanwhile, the knowledge graph is dynamically updated through a graph reasoning algorithm, and the timeliness and accuracy of the knowledge graph are ensured. A more efficient solution is provided for an enterprise in the aspects of management and application of multi-modal data, and the intelligent process of knowledge management is promoted.

The invention relates to the technical field of server scheduling, and discloses a large model reasoning scheduling method based on an off-network computing power server, which comprises the following steps of: collecting hardware information of the off-network computing power server, and constructing a server resource vector; decomposing a large model reasoning task into a plurality of sub-tasks, and constructing task modeling; according to the hardware information of the off-network server and the task dependency relationship, performing task division by using an optimization method; performing dynamic task scheduling on the sub-tasks based on the current load state of the server; according to the real-time calculation load of the server, dynamically migrating part of tasks to other servers to ensure the load balance among the servers; and executing the distributed task, monitoring the running state of the server and the task completion condition, and dynamically adjusting a task distribution strategy according to feedback data. Through modeling task requirements and server resources, in combination with real-time monitoring and optimal scheduling, efficient calculation and resource utilization maximization of large model reasoning in an off-network environment are realized.

The invention discloses a control system for a photovoltaic energy storage inverter, and the system comprises a maximum power point tracking module which is used for adjusting the output of a photovoltaic panel after the photovoltaic energy storage inverter receives a power input signal, optimizing the energy collection, a dynamic adjustment module which is used for adjusting the output of the photovoltaic panel based on the power grid fluctuation and load change parameters which are monitored in real time, the control system of the photovoltaic energy storage inverter comprises a control module used for dynamically adjusting the output frequency and voltage of the inverter and achieving efficient conversion and matching of electric energy, and a closed-loop feedback module used for continuously adjusting the output parameters of the inverter until the output parameters reach a preset energy conversion efficiency threshold value. The system is ensured to be always in an optimal operation state, and unpredictable factor changes are accurately and intelligently adapted, so that the overall conversion efficiency of the photovoltaic energy storage system is improved.

The invention discloses a robot vision inertial navigation method and device and a storage medium, and belongs to the technical field of mobile robot navigation, and the navigation method comprises the following steps: measuring motion information of a mobile robot by using an IMU sensor; collecting image data of the mobile robot by using a camera; inputting the feature points and the descriptors into a LightGlue network model to obtain a local feature point matching relation of the image; calibrating the offset of the gyroscope by optimizing and recovering visual scale information, and estimating the IMU coordinate system speed, the gravitational acceleration and the offset of the IMU; introducing a visual feature re-projection error, an IMU pre-integration error and marginalized residual constraint, and then integrally converting into a target function to obtain a nonlinear optimization result; further repositioning is carried out to obtain a repositioning result; and optimizing the global pose map to obtain a final global pose map optimization result, and carrying out navigation operation according to the global pose map optimization result. The method can improve the positioning precision and operation efficiency under view angle change and illumination change, and is high in practicality.

The invention discloses a dynamic allocation management system for monitoring computing power resources in real time, relates to the technical field of computing power resource management, and is used for solving the problem that an existing dynamic allocation management system for the computing power resources cannot efficiently match, optimally utilize, accurately evaluate and dynamically allocate heterogeneous computing power resources. Comprising a central cloud and a plurality of edge nodes in communication connection with the central cloud, and a real-time monitoring prediction unit, a dynamic distribution management unit and a fault detection processing unit are arranged in the central cloud; according to the method, the utilization rate and delay information of the heterogeneous computing power resources are analyzed in detail, so that the resources most suitable for the target processing task can be efficiently matched; by eliminating the computing power resource with a relatively low delay value, the utilization efficiency of the whole resource is improved, and resource waste is avoided; and resource demand prediction is performed in combination with a plurality of parameters, so that the performance and value of the computing power resources to be allocated can be evaluated more accurately. And effective management and optimal utilization of heterogeneous computing power resources are realized.

The invention relates to the technical field of energy supply and demand matching analysis, in particular to a cross-regional energy supply and demand big data intelligent matching system, which comprises the following modules: a data acquisition module which is responsible for collecting energy supply data and demand data of each region; the data processing module is used for cleaning, integrating and analyzing the collected data, and predicting future energy supply and demand conditions of each region by utilizing a machine learning algorithm; the intelligent matching module is used for intelligently matching an optimal energy supply and demand scheme according to an analysis result of the data processing module; the scheduling instruction module is used for sending a scheduling instruction to the energy management center of each region to realize cross-region allocation of energy; and the feedback adjustment module is used for collecting feedback information, adjusting algorithm parameters and optimizing a matching scheme according to an actual allocation effect. According to the invention, the optimization of energy distribution is ensured, and the loss and cost in the energy transmission process are reduced.

The invention provides a dual-fuel combustion nozzle which comprises a nozzle shell connected with a cooling plate. A hydrogen fuel gas collecting cavity and a liquid hydrocarbon fuel pipe which are coaxial are arranged in the nozzle shell; a first air channel is formed between the inner wall of the hydrogen fuel gas collecting cavity and the liquid hydrocarbon fuel pipe, and a swirler is arranged in the first air channel; a second air channel is formed between the outer wall of the hydrogen fuel gas collecting cavity and the inner shell of the nozzle shell; a liquid hydrocarbon spray hole is formed in the outlet end of the liquid hydrocarbon fuel pipe and is positioned in a space formed by the expansion section of the venturi structure; a hydrogen spray hole is formed in the side wall, close to the top end, of the hydrogen fuel collecting cavity. The invention further provides an engine combustion chamber comprising the combustion nozzle. According to the invention, efficient mixing of hydrocarbon fuel and hydrogen fuel can be realized, the phenomenon of backfire spontaneous combustion is avoided, the flameout boundary is widened, and stable switching of multiple working modes is realized.

The invention discloses an intelligent hospital guide method and system based on symptom matching and department recommendation, and the method comprises the following steps: receiving a multi-modal symptom description inputted by a user, and carrying out the combined processing, thereby obtaining multi-modal symptom information; inputting the multi-modal symptom information into a multi-modal symptom deep learning model to obtain text key symptom features and voice key symptom features, and performing feature fusion to obtain comprehensive symptom feature representation; performing multi-dimensional matching according to the comprehensive symptom feature representation to generate a candidate department list; acquiring the real-time position of the user, inputting the real-time position of the user, the candidate department list and the voice key symptom features into a department recommendation model together, outputting a recommended department by calling a # imgabs0 # minimum spanning tree path algorithm, and generating a department information graph for the recommended department; and displaying department information, a doctor-seeing path and an appointment mode for the user through the department information atlas, thereby realizing intelligent hospital guide. According to the invention, the symptom information of the user is accurately identified and efficient matching with related departments is realized.

The invention discloses an intelligent traffic asset data management method and system, and relates to the technical field of data management, and the method comprises the steps: carrying out multi-dimensional analysis to determine a data classification target label, constructing a machine learning model, obtaining an intelligent data classification model, and carrying out the recognition and classification of asset data. Generating a data label to label data in the traffic asset database; establishing a response association relationship between the traffic asset data and a data application scene, and performing data label dependency and transparency analysis to obtain a data calling constraint; and searching and filtering in the traffic asset database according to the data label in the data calling constraint, and outputting scene application data. The technical problems that in the prior art, due to the fact that the incidence relation between data and application scenes cannot be preset in the data management process, search condition setting is complex, data matching is not accurate, and omission exists during data query and application are solved, and the technical effect of improving data management efficiency is achieved.

The invention discloses a video recognition method based on dynamic space-time full-scale feature fusion, which comprises the following steps: a video data set used for training a deep neural network model is acquired, the video data set comprises a plurality of video sequences, and each video sequence is composed of a plurality of time frames; training a pre-defined video recognition deep neural network model by using the video data set, wherein the video recognition deep neural network model comprises a parallel space-time adapter and a self-prompt generator; and applying the trained video recognition deep neural network model to a video recognition task, inputting a to-be-recognized video sequence, and outputting a classification prediction result of the video. The method has the advantages that through cooperative work of the parallel space-time adapter and the self-prompt generator, efficient modeling of dynamic changes in the video is achieved, the accuracy and robustness of video recognition are remarkably improved, and the method is suitable for various video recognition tasks such as supervised learning, few-sample learning and zero-sample recognition.

The embodiment of the invention discloses a geo-fence generation and matching method and device, electronic equipment and a storage medium. The method comprises the steps that intersecting hash rectangles of a target area are searched step by step according to the sequence of levels from high to low; for the searched intersecting Hash rectangles of each level, after the intersecting Hash rectangles of the current level are found, determining target intersecting Hash rectangles based on the intersecting Hash rectangles of the current level and target accuracy; and determining a fence hash code corresponding to the target area based on the target intersection hash rectangle, and generating a geo-fence of the target area based on the fence hash code, wherein the intersected Hash rectangles are geographical Hash rectangles intersected with the boundary of the target area, the area represented by the highest-level geographical Hash rectangle is the largest, and the area represented by the lowest-level geographical Hash rectangle is the smallest. According to the embodiment of the invention, the geo-fences of the target area with relatively small data volume can be quickly and accurately generated, and the matching process of the geo-fences can be quickly and efficiently carried out with relatively small calculation amount.

The invention relates to the technical field of park investment attraction, in particular to a production research and development project and park matching degree evaluation method and system, and the method comprises the steps: obtaining the target demand data of a production research and development project, and constructing a production research and development project demand map; obtaining park space feature data, and constructing a park space feature map; obtaining the number of isomorphic sub-graphs by adopting a sub-graph isomorphism algorithm; and according to the number of the isomorphic sub-graphs and a matching degree scoring formula, evaluating the matching degree between the park spatial features and the production research and development project requirements. According to the method, accurate matching is carried out by utilizing a subgraph isomorphism algorithm through the constructed production research and development project demand map and the park space feature map, a quantitative matching degree score is provided, and the matching degree between park space features and production research and development project demands is evaluated, so that an enterprise is helped to efficiently match a proper park space, and the production research and development project demand matching efficiency is improved. And more scientific and reasonable decision support is provided for enterprises.

The invention provides a photovoltaic energy storage air conditioning system and a power supply control method thereof. The power supply control method comprises the steps that the generating capacity W of a photovoltaic module, the stored electric quantity Z of an energy storage device and the total load demand electric quantity Q of a unit are obtained; when W is smaller than Q, according to the ratio of W / Q, the energy storage device is selected to supply power to a preset high-power load and a preset low-power load in the unit, or the photovoltaic module is selected to supply power to the preset low-power load in the unit; the photovoltaic technology is applied to the air conditioning unit, clean energy solar energy is used for supplying power, dependence on traditional energy is reduced, and energy consumption is remarkably reduced; and meanwhile, electric energy generated by the photovoltaic module is reasonably utilized, efficient operation of the air conditioning unit under different working conditions is ensured, and maximum use of the electric energy is achieved.

The invention relates to the technical field of intelligent recruitment matching, and particularly discloses an intelligent voice interaction recruitment matching method and system based on a large language model, and the method comprises the steps: receiving recruitment demands and interview questions uploaded by a recruitment end, and storing the recruitment demands and interview questions in a knowledge base; receiving a job hunting request which is uploaded by a job hunter and contains resume information, retrieving the knowledge base based on the resume information, and screening out a matched recruitment end; sending the matched recruitment end as a recommended post to the job seeker, and receiving a selection request of the job seeker; an interview environment is created based on interview questions in the knowledge base, interview is performed on the job seeker, and an evaluation result is generated; and generating an interview condition oriented to the recruitment end and job hunting suggestions oriented to the job hunters based on the evaluation result. According to the invention, the matching degree between the job seeker and the post is improved, the occurrence of invalid interviews is reduced, the job seeker is helped to better prepare interviews, the interview passing rate is improved, the recruiter can more quickly screen out proper candidates, and the recruitment efficiency is improved.

The invention relates to a sea area management and control early warning evidence obtaining method based on video intelligent analysis, and the method comprises the steps: collecting equipment parameters: collecting internal and external parameters of equipment and environment parameters; equipment screening control is carried out, controllable and controllable equipment with a good detection effect is selected through equipment state analysis and target detection effectiveness analysis, and follow-up monitoring of a target area is realized through pan-tilt control; performing video intelligent analysis, determining a follow-up concerned target through mapping matching of a video intelligent analysis model and different coordinate system positioning information, and performing accurate linkage and video snapshot by fine tuning equipment; according to early warning and evidence obtaining association, structured attribute analysis is performed on a target and an area detected in a video capturing process, and an evidence obtaining result is added to early warning information with an association relationship, so that repeated evidence obtaining is avoided. According to the invention, the accuracy and efficiency of early warning evidence obtaining can be effectively improved, the utilization efficiency of data and resources is improved, and powerful technical support is provided for sea area management and control.

The invention relates to a new media anchor matching recommendation system and method based on deep learning and data analysis, which has the effect of improving the matching accuracy and effectiveness of a product and a new media anchor, and comprises the following steps: screening historical purchase orders about to-be-marketed product information from a commodity marketing database; the to-be-marketed product information comprises a product name; calculating a first proportion of the number of times that each feature tag appears in the historical purchase orders to the number of all the historical purchase orders; generating a key feature tag set by using the feature tags of which the first proportions exceed a preset proportion; distributing an initial weight value for each feature tag in the key feature tag set based on the size of the first proportion of each feature tag; generating a real weight value of the reference feature tag; calculating the matching degree of the concerned user information of each new media anchor based on the real weight value of each feature tag and the concerned user information of each new media anchor in a new media anchor database; and sorting and generating a recommended new media anchor sequence according to the matching degree.

The present invention belongs to the field of medical image processing, and provides a method, system and medium for processing medical endoscopic images based on GPU. The present invention utilizes the powerful parallel processing capability of GPU to significantly improve the speed and accuracy of endoscopic image acquisition, preprocessing, feature point detection, image correction and pathological feature recognition. The image quality is enhanced by executing GPU-accelerated filtering algorithms and histogram equalization, while the GPU-optimized SIFT algorithm effectively improves the accuracy of feature point matching. The estimation of the affine transformation model and the transformation correction of the image further correct the distortion and ensure the accuracy of the image data. Finally, the pre-trained deep learning model is used to implement fast convolutional neural network forward propagation on the GPU, identify pathological features in real time, and assist clinical diagnosis. The efficiency and accuracy of clinical diagnosis are greatly improved, providing doctors with instant diagnostic assistance, thereby improving the quality of medical services.

The invention discloses a comprehensive guarantee order dispatching method and system for a large-scale business scene, and relates to the task distribution and data processing technology, and the method comprises the steps: obtaining a to-be-dispatched order, and enabling any order to be distributed to a corresponding vehicle; establishing a dynamic vehicle path planning problem DDVRPTW model with a time window according to the vehicle condition, the road network condition and the user demand when the vehicle executes the order task; establishing constraint conditions according to actual orders and vehicle conditions; for different order dispatching scenes, selecting a corresponding adaptation algorithm to solve the DDVRPTW model; and according to a solving result, the order to be dispatched is dispatched. According to the method, the dynamic vehicle path planning problem model with the time window is constructed, the spatial-temporal constraint and the dynamic disturbance of the guarantee task are accurately described and displayed, and efficient matching of resource demand and supply is realized.

The invention relates to a picometer-level surface shape measuring device for a large-aperture optical element. The picometer-level surface shape measuring device comprises a laser, a first polarization beam splitter, a first acousto-optic modulator, a second polarization beam splitter, a quarter-wave plate, a beam expander group, a local gating measuring surface unit, a 45-degree reflector, a second acousto-optic modulator, a non-polarization beam splitter and a photoelectric detector. The invention further provides a picometer-level surface shape measurement method for the large-aperture optical element, high-precision phase information is obtained based on the double-frequency heterodyne interference principle, regionalized scanning is achieved on the surface of the measured optical element through the local light gating module, and full-aperture high-resolution surface shape measurement can be completed without depending on a mechanical moving platform. The device has the advantages of high mechanical error resistance, high measurement precision, simple system structure and the like, and is suitable for surface shape detection of ultrahigh-precision optical elements.

The present invention proposes a scientific research project expert matching method based on dynamic academic cooperation network graph representation learning, aiming to improve the efficiency and quality of expert matching in scientific research project management. By constructing a dynamic complex network graph, taking scholars as nodes and cooperation relationships as directed edges, this method comprehensively considers the scholars' past research history and cooperation experience. Using graph structure learning and Transformer architecture, feature vector learning is performed on scholar nodes to achieve accurate matching between scientific research projects and experts and scholars. This method has achieved a matching accuracy of more than 80% and a standardized discounted cumulative return of more than 89% on data sets in the fields of artificial intelligence and data mining, effectively solving the limitations of existing technologies in computing costs and the use of scholar feature information, and providing an innovative solution for recommending suitable collaborators for scientific research projects.

This invention relates to the field of visual inspection, and more particularly to a method and system for visual positioning of a bottle. The method is used to perform pose positioning of a transparent bottle. First, in response to the bottle's positioning, a pre-configured ring light source is activated to provide supplementary illumination and a photographing command. Then, in response to the triggering of the ring light source and photographing command, an image of the bottle is acquired. Next, the bottle image undergoes de-reflection and enhancement processing to obtain a feature-enhanced image. Then, feature extraction is performed on the feature-enhanced image to obtain multi-scale features containing the bottle's outline and local features. These multi-scale features are matched with preset template features. If the matching result is satisfactory, abnormal features in the multi-scale features are removed to obtain corrected features. Finally, the corrected features are input into a preset bottle pose algorithm to obtain pose parameters that are applied to downstream devices for alignment. Compared to existing technologies, this invention achieves precise positioning of transparent bottles.

The invention discloses an R + tree dynamic publishing and subscribing method based on a lazy updating strategy. The method comprises the following steps: constructing a subscribing condition list and an R + tree; receiving a subscription condition; generating a unique identifier of the subscription condition, and determining an update field, a boundary field and a pointer field of the subscription condition; judging whether the initialized subscription condition list contains unique representation or not, if yes, deleting the subscription condition, and receiving the next subscription condition; if not, determining an updated subscription list and an updated R + tree, responding to the publishing request of the target event, and receiving a subscription relationship of the target event; and searching in the updated subscription list and the updated R + tree based on the subscription relationship, determining a final target subscription condition, and publishing a final event corresponding to the final target subscription condition. According to the invention, the efficiency of traffic event matching and node subscription management can be improved.

The application provides a backside incidence and top reflection integrated fiber-waveguide coupler, which comprises a substrate, an SOI substrate, a linearly variable grating device, a reflection cavity structure, a lens focusing fiber and a fiber fixing assembly, wherein the SOI substrate is arranged on the top surface of the substrate, the linearly variable grating device is arranged on the SOI substrate, the reflection cavity structure is arranged above the grating waveguide in the linearly variable grating device and is used for reflecting the uncoupled light back to the grating area to enhance the coupling efficiency, and the lens focusing fiber and the fiber fixing assembly are arranged on the back surface of the substrate, so that the incident light signal enters the grating waveguide part of the grating area through the back surface of the substrate at a preset inclination angle. The fiber-waveguide coupler of the application can improve the coupling efficiency, widen the coupling bandwidth, release the front surface space of the chip, and is beneficial to high-density photon integration and low-temperature environment application.

The invention discloses a full-hydraulic full-circle needle beam trolley and method for compressed air energy storage, and relates to the technical field of beam trolleys, the full-hydraulic full-circle needle beam trolley further comprises a moving frame, the moving frame is fixedly connected to the interior of a frame assembly and arranged on the outer side of a needle beam assembly in a sleeving mode, a sliding rail is fixedly connected to the outer side of the needle beam assembly, side grooves are formed in the two sides of the moving frame, and the sliding rail is fixedly connected to the sliding rail; a containing groove is formed in the bottom of the movable frame, a plurality of sliding blocks used for sliding are arranged between the movable frame and the sliding rail, and mounting pieces are arranged between the sliding blocks and the movable frame. A displacement sensor in the detection mechanism can accurately measure the actual abrasion depth of the bottom of the sliding block, and therefore distributed and normalized monitoring of the abrasion state of the sliding block is achieved. When it is monitored that the abrasion loss of any sliding block reaches the preset highest threshold value, the system can give out early warning in time to remind an operator to replace a specific sliding block, risks such as equipment clamping stagnation, precision reduction or sudden failure possibly caused by excessive abrasion of the sliding block are avoided, and construction safety and continuity are guaranteed.

The present invention discloses a heat storage device, an energy supply system and a method for rapidly increasing the load of a coal-fired power generation unit, and relates to the technical field of rapid peak regulation of coal-fired power generation. Aiming at the problem that the steam production rate of the boiler of a coal-fired power generation unit is insufficient under low-load operation conditions, resulting in the limited load change rate of the unit, the present invention provides a high-temperature and high-pressure water heat storage device and its energy supply system that can improve the rapid load increase capacity of boilers of various grades of coal-fired power generation units. When the unit is in stable operation or load reduction at medium and high loads, the abundant steam energy is stored in the high-temperature and high-pressure water heat storage device through indirect heat exchange. When the unit is in a low-load condition and needs to climb rapidly, the water heat storage device directly supplies high-enthalpy steam and saturated water to the boiler steam-water system. Since there is no fuel heat release and working medium heat absorption process in the energy supply process, the problem of boiler heat transfer hysteresis is fundamentally solved, thereby directly and rapidly improving the boiler steam production rate and realizing rapid load increase of the coal-fired power generation unit.

The application provides a service-aware-based dynamic allocation method for carbon satellite ground system resources, relates to the technical field of computing power resource allocation, and comprises the following steps: through analysis, a benchmark task priority distribution of a benchmark task node distribution is obtained, and then a container resource pre-call distribution is output after execution container scheduling timing analysis; a high-load node sequence is projected to the container resource pre-call distribution, and a container resource pre-call sequence is located; after judging the load demand of real-time weather satellite and carbon satellite data streams, the container resource pre-call sequence is triggered to perform timing elastic scheduling of container resources. The application solves the defects of the prior art, such as the rigidity of ground system resource allocation, low utilization rate of task processing container resources, and serious delay of carbon satellite monitoring data processing. The application achieves the technical effects of multi-dimensional resource pre-scheduling strategy and elastic feedback closed-loop control mechanism, realizes dynamic load-driven efficient resource matching, and significantly improves the utilization rate of heterogeneous container resources.

The invention provides a circuit design layout and scanning electron microscope image registration method and device, and belongs to the technical field of semiconductors. The registration method for the circuit design layout and the scanning electron microscope image comprises the following steps: acquiring a first circuit design layout and the scanning electron microscope image, wherein the first circuit design layout comprises a plurality of first graphs; performing image processing on each first graph in the first circuit design layout to generate a scanning electron microscope simulation graph corresponding to each first graph so as to obtain a simulation electron microscope image; and registering the simulated electron microscope image and the scanning electron microscope image to obtain a matching result. The scanning electron microscope simulation scanning graph is close to the scanning graph in the scanning electron microscope image in morphology, so that the scanning electron microscope image and the simulation electron microscope image can be matched efficiently, quickly and accurately, and the matching efficiency and accuracy are improved.

This invention provides a data processing method and related products for graph databases. The data processing method includes: acquiring a document query request; matching multiple candidate document entities in the graph database using graph retrieval based on the document query request; acquiring the document query vector of the document query request; acquiring the content attributes of each candidate document entity, where the content attributes are in vector form and used to represent the content of the corresponding candidate document entity; and using vector retrieval to match one or more of the content attributes of each candidate document entity with the highest similarity to the document query vector, which are then used as the target document entity. In this method, graph retrieval and vector retrieval support and cooperate with each other, achieving the goal of improving the overall accuracy and efficiency of document queries in graph databases.

The present invention discloses an optimization method and service system for precise push based on big data analysis, which relates to the field of human resources technology. In S1, various job requirements and user resume data are collected and integrated in advance to generate a static data set, which provides basic information support for subsequent matching. S2 uses the job matching factor Gpyz to preliminarily screen users and jobs that have not communicated, so as to accurately locate potential compatible target users and target jobs, thereby improving matching efficiency. In S3, the method generates a dynamic data set and monitors the activity level by counting the behaviors of target users and actively interacting users, analyzes the similarity Xsd, and constructs the satisfaction coefficient of active users for various jobs, further enhancing the understanding of job requirements and user preferences. S4 predicts the satisfaction coefficient and combines the evaluation threshold Q for further comparative analysis, so that the system can further screen out candidates that are highly matched with job requirements.