133 results about "Human resource management" patented technology

The invention discloses a job-hunting interview question AI generation method based on a large language model, and relates to the technical field of human resource management, and the method comprises the following steps: S1, analyzing post information, and extracting core skill points; s2, constructing candidate feature matching vectors based on the core skill points; s3, performing knowledge graph expansion by using the core skill points and candidate feature matching vectors; s4, performing semantic fusion on the basis of the extended knowledge graph to obtain a knowledge association set; s5, performing question generation and difficulty grading by using the knowledge association set; and S6, performing logic consistency detection and diversification generation by using the question set. By setting knowledge graph extension and semantic fusion based on post core skill points and candidate feature matching vectors, a knowledge association set with a wider coverage and a more reasonable structure can be established before topic generation, and it is ensured that the extended knowledge graph not only embodies post requirements but also is matched with candidate features.

The invention discloses a human resource production and teaching fusion supply and demand matching system based on a dynamic ability portrait, and relates to the field of human resource management. Comprising a capability analysis module, a structure modeling module, an occupational mapping module, a selection monitoring module, a path generation module, a behavior analysis module, a task matching module, a supply and demand evaluation module, a guide iteration module and a recruitment screening module. According to the method, capability portraits do not depend on subjective resumes any more, the accuracy and credibility are remarkably improved, the problem that a static label model cannot reflect a real growth track is solved, the competency and potential rising space of talents for posts can be more accurately judged, the problem that traditional HR cannot process cross-domain task matching is solved, and the method is suitable for popularization and application. And real-time closed-loop alignment of supply and demand of production and education is realized.

The invention relates to the technical field of artificial intelligence and human resource management, and discloses an intelligent talent matching method and device based on a dynamic post portrait, equipment and a storage medium, which are used for improving the accuracy of talent matching and the system adaptability. The intelligent talent matching method based on the dynamic post portraits comprises the steps of obtaining post description and candidate skill information, performing semantic enhancement processing on post texts through local and global attention mechanisms, and constructing the dynamic post portraits; performing similarity comparison on the post portraits and candidate skills, and screening out primary candidate subsets; then, precise matching degree prediction is achieved through deep interactive calculation, and a recommendation list is generated; user feedback data and industry trend information are continuously collected, a closed-loop learning mechanism is established, and dynamic adjustment and continuous optimization of post portraits are achieved.

The invention provides an intelligent interview system and method, and relates to the technical field of online recruitment and human resource management, and the system comprises a data collection layer, a capability evaluation engine layer, a process control layer, a safety monitoring layer, a report generation layer and an event bus. According to the invention, through evaluation and fusion of multiple capability dimensions such as competency, programming capability, mandarin capability, professional / basic capability and the like, objectivity of an evaluation result is improved; the comprehensiveness of cheating protection is improved through continuous verification and multi-modal cross comparison in the answering process; through event driving and a state machine model, manual intervention and the abnormal failure rate are reduced, and intelligent management and control of the whole process are achieved; and through decoupling of a report template and a division caliber and implementation of versioning management, historical traceability and multi-enterprise differentiated delivery are realized.

The invention discloses an employee performance evaluation method based on behavior data driving, and relates to the technical field of human resource management, and the method comprises the following steps: constructing a multi-channel network fluctuation prediction matrix, generating an expected behavior arrival time scale based on the transmission state of a task switching node, and taking the expected behavior arrival time scale as a baseline for behavior sequence gap recognition; and under the guidance of an expected behavior arrival time scale, performing sliding window scanning on the received behavior sequence, generating a gap identifier when detecting that a time slot exceeds a threshold value, and injecting a confidence coefficient weight descending label. According to the method, a behavior gap is accurately identified through network fluctuation prediction and sliding window scanning, behavior reconstruction is realized in combination with self-supervised generation and residual reasoning, and dynamic evaluation correction is completed by using confidence projection and an intelligent regulation engine, so that the data authenticity is guaranteed from the source, and the objectivity and robustness of performance evaluation and the resource allocation precision are improved.

The invention provides a personnel portrait construction method and system based on a multi-dimensional talent evaluation model, and belongs to the technical field of human resource management and data processing, and the method comprises the steps: collecting the original data of talents, constructing a tree-level comprehensive quality index system, and outputting the index score vectors of the talents; performing dimension reduction processing on the original data to extract key features, calculating objective weights of the key features, and outputting weight vectors; inputting the key features and the weight vectors into a random forest machine learning model to calculate a preliminary evaluation score; on the basis of the key features, an analytic hierarchy process is adopted to calculate expert correction scores; integrating the two scores to calculate a comprehensive evaluation score, and constructing a personal portrait based on the index score vector, the comprehensive evaluation score and the key features; and updating the personal portrait, monitoring the index score vector or the comprehensive evaluation score, and generating growth early warning information for the talents meeting the early warning conditions. According to the method, multi-dimensional data are integrated, the weight is objectively calculated, and the portrait is dynamically updated.

The application relates to the technical field of human resource management, in particular to a medical staff scheduling system based on medical staff skills, which comprises a standard skill input and classification device, which is used for inputting the working skills of each department, dividing the same working skills of each department into general skills, and dividing the special working skills of each department into special skills; a department patient input device, which obtains the treatment information of patients in each department ward, extracts the predicted workload of each patient in the next scheduling cycle, and counts the predicted workload of each department; the predicted workload comprises the execution times of each general skill and the execution times of each special skill; the system realizes cross-department dynamic scheduling by constructing a hospital-level skill resource pool and a demand prediction mechanism, standardizes the general skills into shared resources, and enables medical staff to flexibly support departments with high demand peaks.

The utility model relates to the technical field of file frame, and disclose a kind of human resource management file frame, including file frame main part, the bottom of file frame main part is connected with placing box, the inside rotation of placing box is connected with damp-proof mechanism, the bottom fixed connection of file frame main part has support leg, the surface of support leg is equipped with placing plate, the surface of placing plate is equipped with heating mechanism, damp-proof mechanism includes the rotation of rotating rod in the inside of placing box.The human resource management file frame, through the setting of damp-proof mechanism, when using, file frame main part bottom is installed placing box by bolt, rotating is carried out using driving motor to drive the discoloration silica gel desiccant in placing box interior, so that water absorption surface is located in file frame main part interior, cooperate the gas hole of being set in file frame main part interior several, to realize to file frame main part interior carries out damp-proof treatment, avoid the file in file frame main part interior to be damp and mouldy.

The utility model discloses a human resource management holeless file folder, which belongs to the technical field of file folders, and comprises a hard-shell cover, a disassembly assembly is arranged on the inner side of the hard-shell cover, and a clamping assembly is arranged on the upper surface of the disassembly assembly; the rotating handle is rotated to drive the rotating screw rod to rotate, the upper clamping plate is driven to move downwards to clamp and fix a paper file placed on the bottom plate under the cooperation of the limiting rod, the friction force with paper is increased through the multiple rubber strips, and the paper file is prevented from sliding in the clamping process; according to the file folder, the rubber strip is pulled out through cooperation of the T-shaped sliding block and the T-shaped sliding groove so as to be replaced, the bottom plate is installed on the hard shell cover through cooperation of the threaded sleeve and the threaded rod, fastening or loosening operation can be achieved through rotation, different parts of the file folder can be detached, and cleaning, maintenance or damaged part replacement are facilitated; the practicability and flexibility of the device in use are improved, and the service life of the whole device is prolonged.

The invention relates to the technical field of human resource intelligent management, in particular to a post competency grading evaluation method and system based on a capability quality atlas, and the method comprises the steps: obtaining basic data of a target post, extracting a capability feature vector, and dynamically generating a model through the atlas, acquiring a post exclusive capability quality map containing capability dimension levels and behavior anchor point standards; obtaining data of an object to be evaluated, obtaining a capability item efficiency score through a capability item quantification model, obtaining a comprehensive competency index through a competency depth coupling model in combination with a behavior anchor point standard, and obtaining a post competency fitness value of the object to be evaluated through a post competency decision-making model in combination with a capability dimension level; and performing post competency grading evaluation by adopting an interval mapping technology, and outputting an interval grading result. According to the scheme, post competency grading can be carried out, standardization, objectification and individuation of competency evaluation are achieved, and efficient and accurate technical support is provided for enterprise talent development.

Processing Device for Human Resource Management Data Analysis

The application discloses a kind of multi-dimension resume intelligent screening and post matching method based on large model, it is related to artificial intelligence and recruitment technical field.The method includes: resume and post information are preprocessed and standardized;Using recruitment field fine-tuning large model, combined with knowledge graph, hierarchical attention mechanism and BiLSTM-CRF structure, extract the multi-dimension feature of resume and post;By cosine similarity, analytic hierarchy process and hungarian algorithm, construct matching model, realize global optimal matching;Adaptive threshold is used to complete final screening and output matching result.The application can significantly improve resume screening efficiency and matching precision, solve the problems of traditional mode such as insufficient semantic understanding, one-sided feature extraction and simple matching logic, suitable for various enterprise recruitment and human resource management scenarios, with high practicality and popularization value.

The invention discloses a human resource management service system based on Internet of Things, and relates to the technical field of Internet of Things and human resource management, and the system comprises a data collection module, a data analysis module, a data processing module and a local database, and is used for collecting customer service center environment, employee physiological behaviors and business multi-source data; according to the method, regional load and health risks are evaluated in two dimensions, a visual risk distribution diagram is generated, future overload risk levels are pre-judged, differentiated environment intervention and cross-regional task scheduling are matched, health intervention strategies are matched, the intervention effect is quantitatively verified through correlation analysis, a data splitting barrier is broken, accurate and preventive intelligent management and control of human resources of a customer service center are achieved, and the risk assessment efficiency is improved. Employee fatigue is effectively relieved, and resource allocation efficiency and customer service experience are remarkably improved.

The invention provides a talent flow analysis method based on population data. The talent flow analysis method comprises the steps of obtaining talent big data; based on a pre-trained talent flow analysis model, performing talent flow analysis according to the talent big data to obtain an analysis result; and outputting and displaying the analysis result. According to the talent flow analysis method based on the population data, accurate description and foresight prediction of the talent flow condition are achieved, powerful data support is provided for government talent policy making, enterprise human resource management, personal occupational planning and the like, talent resource configuration optimization is facilitated, and talent efficiency is improved.

This application provides a multi-source collaborative personnel recruitment processing method, system, computer equipment, and readable storage medium. The method includes: a recruitment approval system acquiring candidate data from a human resources management system and office building data from an infrastructure system based on a data interface and ETL method; the recruitment approval system triggering a query process based on the acquired data and initiating political review and access card processing matters to the infrastructure system; the query process including at least one of the following: professional reputation query process, integrity query process, and background investigation process; after the query process is completed, the document system triggering a stamping process to call the electronic seal system; the electronic seal system electronically stamping the relevant documents involved in the query results of the query process to generate recruitment approval data; and feeding back the recruitment approval data and the query results to the human resources management system.

The application discloses an intelligent matching method and device, computer equipment and a storage medium. The method comprises: obtaining input query information; analyzing and enhancing the query information through a fine-tuned large language model, and converting the query information into a structured multi-dimensional demand vector; extracting a feature vector matched with the query information from a preset resume by using an attention mechanism to obtain an extraction result; calculating the matching degree of each dimension based on the extraction result and quantifying the residual error, and performing candidate screening and sorting according to a set rule to obtain a matching result; and generating a natural language report based on the matching result, wherein the natural language report comprises an overall evaluation, advantage analysis, risk interpretation and personalized suggestions. The method of the application can realize deep semantic understanding, quantitative matching gap, and intelligent decision support, thereby meeting the needs of modern human resource management.

This invention discloses a data processing method and system for human resource management, comprising the following steps: S1, acquiring multi-source heterogeneous data and preprocessing it; S2, merging the states of business features within a sliding time window and constructing a business relationship graph based on the transition relationships between state nodes; S3, modeling continuous transition relationships based on the business relationship graph, and performing segmentation identification and parameter reestimation; S4, performing high-order neighborhood coupling orchestration and constraint segmentation on each transition link, while simultaneously performing structural compression and order rearrangement to generate high-order linkage responses; S5, rearranging the execution intensity of linkage states based on high-order linkage responses and orchestrating the management order to obtain a management action sequence; S6, acquiring execution feedback data and jointly updating the link weights and dynamic transition parameters. This invention can realize the correlation modeling of multi-source business data in human resource management scenarios, improving the orderliness of management action arrangement.

The invention discloses a human resource integrated management platform system which comprises a basic data standardization module which is used for establishing a data standard system in the whole field of human resource management. Standardized definition, format specification and verification rule setting are carried out on employee basic information, organization structure information, post information, salary and welfare information, attendance information and performance information, and unified collection, storage and sharing of data are achieved. The method has the beneficial effects that based on a basic data standardization module, all-field data standards are unified and automatically checked, data redundancy and errors are eliminated, cross-module data integration is smoother, and the efficiency of basic transactions such as salary accounting and attendance statistics is improved; the multi-dimensional intelligent analysis module integrates data and applies big data and a machine learning algorithm, not only generates a basic analysis report, but also can accurately predict employee demission risks, outputs decision suggestions such as retention, training optimization and the like, and assists enterprise data-driven management.

The invention discloses enterprise internal human resource management digital management and a construction method thereof, and belongs to the technical field of enterprise digital management. Comprising an employee management module, an information processing terminal and an information maintenance module, the employee management module is in communication connection with the information processing terminal, the employee management module is in communication connection with the information maintenance module, and the information processing terminal is in communication connection with the information maintenance module. The problems that in the prior art, an information management system used by an enterprise institution and the like generally only pays attention to function design, lacks attention of an actual business scene, is difficult to synchronously express operation of full-scene business of the enterprise institution in a twin digital space, cannot realize intelligent management of the enterprise institution, and is inconvenient to use can be solved. And the management efficiency of enterprise institutions is limited.

To provide an information management system or the like capable of properly managing a personnel management document.SOLUTION: According to an aspect of the present invention, there is provided an information management system, including at least one processor, the processor being configured to execute the following steps by reading a program: In the creation step, a first document related to a human resource management document including a document component derived from the registration information is created, the document component including a sentence created based on the registration information, and in the disclosure acceptance step, a disclosure request for disclosing the first document or a compilation of the first document in a predetermined range is accepted from the managed person and / or a manager of the managed person, in the disclosure step, the first document or the compilation is disclosed in a predetermined range as a human resource management document on the basis of reception of a disclosure request.SELECTED DRAWING: Figure 1

This invention discloses a resume screening and display method and system for human resource management. It constructs a keyword-dimension mapping table based on job description text using a natural language processing engine; analyzes keyword frequency, syntactic position, modification strength, and semantic relevance to generate a job requirement intensity vector; retrieves historical recruitment data based on job meta-information to generate a historical weight vector; adaptively calculates a smoothing coefficient based on the amount of historical data; and integrates dual-source weights to generate a dynamic weight vector; standardizes the scoring of each dimension of the resume, using a normalized formula based only on valid dimensions to calculate the matching degree, avoiding score distortion caused by missing fields; and finally displays the results sorted by matching degree. This invention abandons the preset weight mode, achieving dynamic screening with a tailored approach for each job, improving matching accuracy, operational efficiency, and the quality of human-machine collaborative decision-making, providing a scientific, efficient, and transparent intelligent solution for human resource management.

This invention discloses a human resource intelligent planning method and system based on big data analysis, relating to the field of human resource management. It includes constructing a two-layer storage architecture of a human resource data lake and a data warehouse; extracting basic features from the data in the data warehouse using multi-dimensional features; selecting features strongly correlated with human resource needs from these basic features to construct a knowledge graph and then mining hidden correlation features; building a multi-model fusion prediction model to output prediction results; based on the prediction results, using an improved non-dominated sorting genetic algorithm to optimize human resource allocation and obtain a human resource allocation strategy pool; introducing digital twin technology to construct a digital twin model of enterprise human resources and business scenarios; simulating the implementation effect of the human resource allocation strategy pool for comprehensive evaluation; and determining the target human resource allocation strategy based on the comprehensive evaluation. This invention improves the accuracy of human resource demand prediction and the adaptability of planning by employing the above method, while reducing human resource costs and manual maintenance costs.

The invention discloses a human resource management method and system based on artificial intelligence, and relates to the technical field of human resource management, and the method comprises the following steps: guaranteeing personal data sovereignty through an employee side personal data insurance library and homomorphic encryption; the method comprises the following steps: constructing double agents which belong to employees and organizations and represent respective interests, and generating and signing an automatically executed initial bidirectional contract through anti-fact simulation and game theory negotiation; during the duration of the contract, the employee intelligent agent monitors the multivariate contribution in real time, and adjusts the contract terms according to a dynamic formula; dynamic value measurement and distribution of multi-element contribution are realized by combining causal reasoning interpretable analysis and a Shapley value algorithm through a federated learning cooperative training model integrating differential privacy and homomorphic encryption; by constructing a full-link privacy architecture, a bidirectional agent negotiation system and alliance chain cross-organization ecology, privacy and data utilization and organization and employee benefit balance are realized, talent ecology is constructed, and management intelligence and fairness are improved.

The invention discloses a human resource information processing system and method, and relates to the technical field of human resource management information processing.A prototype measurement mechanism is introduced into an embedding space, a limited number of labeled samples are aggregated into stable category center representation, dependence on large-scale historical data is reduced, and the accuracy of human resource information processing is improved. Representative high-loss risk and low-loss risk category prototypes can also be formed in sample scarcity scenes such as medium and small enterprises, new business departments or new posts; characteristic embedding is carried out through cooperation of a pre-trained neural network model and transfer learning, the method effectively inherits the general characterization capability in large-scale human resource data, and then a prototype calculation module and two-norm-based normalization processing are superposed, so that feature vectors of different employees or candidates are more uniform in the numerical scale, and the accuracy of the human resource data is improved. The interference of the abnormal sample modulus length difference on the subsequent distance measurement is obviously weakened, so that the numerical stability during the similarity calculation in the high-dimensional embedding space is improved.

The invention relates to the field of human resource management, in particular to a human resource management method based on multi-modal data fusion and adaptive learning, and adopts the technical scheme that the method comprises the following steps: constructing a time sequence data portrait of a target object through static attribute data, dynamic behavior data and external environment data; and inputting the multi-modal data into a preset feature extraction model for feature extraction to obtain a multi-dimensional feature vector, inputting the multi-dimensional feature vector into a pre-trained human resource analysis model to obtain an analysis result, and finally executing a corresponding human resource management operation according to the analysis result. The personnel and post matching degree score, the demission risk probability and the recommended development path are analyzed, intelligent resume screening and personnel and post matching optimization can be carried out, employee demission risk prediction and intervention suggestion can be carried out, personalized employee development path planning can be carried out, and the employee development path planning efficiency is improved. And deep learning and dynamic optimization capabilities are improved through an algorithm framework of multi-modal data fusion and dynamic adaptive learning.

1. The name of the design product: human resource management worktable. 2. The use of the design product: for human resource management related staff office worktable. 3. The design points of the design product: in shape. 4. The picture or photo that best indicates the design points: perspective drawing.

The invention relates to the technical field of artificial intelligence and human resource management crossing, in particular to a human resource intelligent matching method and system based on big data analysis. The method comprises the steps of performing structured node conversion processing on to-be-processed human resource data to obtain a structured node data set; performing organization interaction rule analysis processing on the structured node data set to obtain an interaction force value between the nodes; the organization interaction rule analysis processing is based on a same-frequency resonance rule and a complementary rejection rule, and interaction between nodes in a value dimension and a core capability dimension is analyzed; and performing node recombination arrangement matching processing according to the interaction force value to obtain a human resource arrangement matching result. According to the invention, the human resources can be accurately arranged and matched.

The invention discloses an enterprise human resource management evaluation method and system. The method comprises the following steps: acquiring, analyzing and evaluating management process data to obtain an index evaluation value of each preset monitoring index; determining a weight corresponding to each preset monitoring index, and performing calculation based on the weight and the index evaluation value to obtain an initial evaluation value of enterprise human resource management; obtaining management result data of the enterprise for analysis, and determining result parameter data related to enterprise human resource management; evaluating the enterprise human resource management result based on the result parameter data to obtain a management result evaluation value, and determining a correction coefficient based on the management result evaluation value; and correcting the initial evaluation value based on the correction coefficient to obtain a comprehensive management evaluation value. According to the invention, the transformation of human resource management from an empirical type and qualitative type to a data type and quantitative type is realized, an intelligent evaluation system capable of self-calibration and continuous optimization is established, and powerful technical support is provided for enterprises to improve the human resource management level.

The invention discloses an employment service management method and system based on an AI large model, and relates to the technical field of human resource management, and the method comprises the steps: integrating the semantic embedding of a semantic enhancement substring in a clustering result through weighted average pooling, generating a comprehensive semantic embedding vector of the semantic enhancement substring, and carrying out the semantic embedding of the semantic enhancement substring; calculating semantic similarity of the semantic embedding vector by using cosine similarity, and generating a recessive skill vector; calculating intensity similarity and semantic similarity on the basis of the normalized recessive skill vector, calculating comprehensive matching degree on the basis of the intensity similarity and the semantic similarity, converting the comprehensive matching degree into a cost value by using linear transformation, and solving and generating a pairing set by using a Hungary algorithm. According to the method, key semantic information in job seeker resumes and post description is enhanced by combining a semantic embedding technology and a substring clustering algorithm, and deep semantic understanding of a traditional text matching method is improved by combining semantic feature extraction with weighted average pooling.

The invention discloses a multi-objective decision support system for enterprise human resource configuration, and relates to the technical field of human resource management and intelligent decision. The system comprises a data acquisition module, an employee ability evolution prediction module, a team collaborative effect evaluation module, a matching degree calculation module, a hierarchical collaborative optimization module, a real-time feedback and adaptive update module and a result output module. According to the system, an employee ability growth curve prediction model is established, the cooperative effect between employees is quantified, the competency matching degree, the team cooperation degree, the cost and the ability growth potential are comprehensively considered, a hierarchical collaborative optimization algorithm combining differential evolution and improved ant colony is adopted, and an optimal personnel allocation scheme is generated under multi-target constraints. According to the invention, a new matching degree formula and an optimization algorithm are provided on the basis of considering employee ability evolution and team cooperation, and the system also has a real-time feedback and adaptive updating mechanism, can continuously improve the man-post matching accuracy in a dynamic environment, and achieves the intelligentization and prospect of enterprise human resource management.