248 results about "Human resource management" patented technology

The invention relates to the field of human resource management, and discloses a tobacco enterprise human resource management auxiliary calibration method based on big data, and the method comprises the steps: obtaining multi-source heterogeneous data related to enterprise internal human resources, and constructing a structured human resource data model in combination with a data standardization processing mechanism and an abnormality elimination strategy; post portrait modeling is carried out on the structured human resource data model, a capability dimension nesting analysis method is introduced, key capability factors and weight distribution required by each post are extracted, and a post capability demand graph is constructed; based on the post capability demand map, fusing the staff portraits and the historical job data, and identifying the deviation between posts and the staff through a multi-dimensional feature matching algorithm to form a preliminary calibration suggestion set; and a dynamic service association analysis method is introduced, and key matching parameters in the preliminary calibration suggestion set are dynamically corrected in combination with latest service demand data and real-time task assignment information. The method has the advantage of improving the management efficiency.

The invention discloses an electric power engineering project management talent intelligent evaluation and dynamic training system, and the system comprises a multi-dimensional quality capability model construction module which constructs a four-dimensional capability framework based on the characteristics of an electric power engineering industry, generates a differentiated post capability model through a dynamic weight distribution algorithm, and carries out the dynamic training of the differentiated post capability model; constructing an industry ability dictionary library by utilizing a knowledge graph technology; the intelligent evaluation and matching module integrates a multi-modal evaluation tool to collect dominant and implicit capability data, dynamically adjusts capability index weights through a pre-trained AI model based on project characteristic parameters, and calculates man-post adaptation indexes by adopting a cosine similarity algorithm; and the dynamic training and development module is used for generating a personalized training scheme by quantifying the capability difference, tracking the training effect in a closed-loop manner based on a Korotkoff four-level evaluation model, and dynamically optimizing a training path by adopting a Bayesian network. The technical defects of single evaluation dimension, low man-post matching degree and insufficient cultivation efficiency of traditional power engineering human resource management can be solved.

The invention relates to the technical field of human resource management, and provides a one-stop talent screening method and system. The method comprises the steps of performing text analysis on a job seeker resume, identifying structured information in the job seeker resume, performing weight distribution on the analyzed information through a preset post competency model, and generating a resume analysis result containing a candidate and target post matching degree score; consultation information about enterprise information, position treatment and office environment of the job seeker is obtained, the consultation information is analyzed to obtain a question intention of the user, and response content corresponding to the question intention is generated; performing semantic analysis on the communication record corresponding to the job seeker, and identifying the job hunting willingness level of the job seeker; and dynamically generating personalized interview questions through an interview question generation model in combination with the matching degree score and the job hunting willingness level to complete talent screening. The method is suitable for full-process automatic processing of resume screening, intelligent communication and adaptive interview in the enterprise recruitment process.

The invention relates to the technical field of human resource management, and provides an intelligent paper marking system and method for talent selection and recruitment. The method comprises the following steps: cutting test paper according to a preset test paper template by using an image processing technology to obtain a plurality of plates corresponding to the test paper; converting the image content of each section of the cut test paper into a text format which can be edited and processed by adopting a character recognition technology; setting a preliminary scoring standard according to question type information and knowledge point information corresponding to the test paper, and optimizing the preliminary scoring standard by using a large language model; performing semantic understanding and logic analysis on the converted test paper text answers from a plurality of scoring dimensions including semantic accuracy, logic integrity and knowledge point coverage by using two preset scoring large models to give corresponding scoring information, and marking advantage information and defect information in the answers; and obtaining a comprehensive score corresponding to the test paper according to score information printed by each score big model for each question of each test paper.

The invention discloses a human resource intelligent management method and system based on man-post matching, and the method comprises the steps: receiving an unstructured post description text, extracting key information through a natural language processing technology, generating a structured multi-dimensional post portrait, and classifying the structured multi-dimensional post portrait; on the basis of historical recruitment data, predicting the number of future post demands by means of a time sequence analysis model; for the candidate resumes and the target post portraits, keyword correlation scores, depth semantic similarity scores and predictive stability scores are calculated in parallel; according to the post portrait classification application dynamic weight, performing weighted summation on the scores to generate a comprehensive matching score; and sorting the candidates according to the comprehensive matching scores, and outputting a sorted candidate list. According to the method and the system provided by the invention, the man-post matching accuracy and the recruitment efficiency are effectively improved, the core pain points of intelligent recruitment, man-post matching and demand prediction in human resource management are solved, and the method and the system are particularly suitable for the demands of human resource outsourcing and labor dispatching industries for stable service selection.

The invention provides a matching recommendation method and system based on large-model digital talent inventory, relates to the technical field of artificial intelligence and human resource management, integrates large-model analysis, employee portrait modeling, intelligent matching recommendation and visual display of comparative analysis, has the characteristics of automation, high precision and interpretability, and is suitable for popularization and application. The problems of difficult man-post matching, inaccurate talent evaluation, opaque selection process and the like are solved, and digital talent selection and intelligent decision making are realized.

The invention discloses a query condition analysis method and device and a medium, and the method comprises the steps: receiving a natural language query statement input by a user for a human resource management system, and extracting a core semantic unit in the natural language query statement; based on a preset knowledge base, mapping the core semantic unit into a semantic structure corresponding to an Elasticsearch database to generate a corresponding key vector diagram; based on a preset pseudo code normal form, generating a pseudo code according to the key vector diagram; wherein the pseudo code comprises a query node set and a logical relationship between query nodes; and performing code verification on the pseudo-code, and converting the pseudo-code into a DSL query statement in an Elasticsearch database under the condition that the pseudo-code passes the code verification, so as to realize semantic analysis on the natural language query statement through the DSL query statement.

The invention discloses a man-post matching adaptive optimization system and a method thereof, and relates to the technical field of human resource intelligent management. Comprising the following steps: acquiring post demand data containing experience years, post vacancy days and post types, and candidate ability data containing implicit ability scores; candidate growth coefficients are generated based on post demands; outputting an initial matching degree through data comparison; when the matching degree exceeds a preset threshold value, the implicit capability score and the empirical age limit are converted into a communication value and an empirical value respectively, and a soft compensation coefficient is obtained through weighted calculation; generating a risk coefficient according to the number of post vacancy days, and loading a basic weight according to the post type (if the vacancy exceeds the limit, increasing a second weight); and calculating a comprehensive matching degree and outputting a grading decision instruction. Through coupling growth prediction, implicit capability compensation and a dynamic risk parameter adjustment mechanism, the accuracy and adaptability of man-post matching are significantly improved.

The invention discloses an intelligent recruitment matching platform and method driven by multi-modal behavior data, relates to the technical field of human resource management and intelligent information processing, and is used for solving the problem that efficiency and accuracy of a system are difficult to consider at the same time due to change of the number of links in an existing recruitment process. According to the technical means, multi-modal portraits of posts and candidates are constructed, consistency checking and credibility correction are carried out among links, when the number of links exceeds a threshold value, deep comparison is carried out on abnormal links, simplification processing is carried out on other links, and the threshold value and parameters are continuously adjusted in combination with entry performance feedback. Through the above technical means, false or contradictory information is effectively identified while the processing time is ensured, and the matching accuracy and the stability of the recruitment process are improved.

The invention relates to the technical field of human resource management, in particular to a labor dispatch outsourcing management and intelligent human dispatch outsourcing system, which comprises a process disassembly module, a condition check module, a capability construction module, a connection screening module and a dispatch adaptation module. According to the method, the post task is subjected to nodal sequence processing, digital expression of the post operation process is realized in combination with action labels and operation stage mapping, deviation nodes in the operation process are identified by means of device numbers and sorting verification of operation sections, and the task process precision and the quality control capability are improved; post boundary condition constraint verification is completed by fusing post equipment permission and an operation section period table, the probability of occurrence of task matching conflicts is remarkably reduced, and the coherence consistency of personnel and post actions is improved by comparing behavior tags with a post action sequence, so that accurate matching and efficient coherence deployment of tasks and personnel are realized, and the task matching efficiency is improved. And the intelligence, the matching degree and the performability of labor dispatching are enhanced.

The invention discloses a recruitment full-process automatic cooperation method and system based on a large language model, and relates to the technical field of artificial intelligence and human resource management, and the method specifically comprises the following steps: a recruitment platform receives recruitment position information issued by an enterprise recruiter, and generates a standardized recruitment position information description; performing text semantic analysis on the standardized recruitment post information description, and extracting a job key field of a recruitment post; extracting job seeker resume key fields from the job seeker resume; converting the job key field of the recruitment post into a high-dimensional semantic query vector, constructing a resume semantic vector library based on the resume key field of the job seeker, and performing query matching to generate a candidate resume list set; generating an interview comprehensive evaluation report based on the interview data; returning the interview comprehensive evaluation report to a training library of the large language model, and updating parameters of the large language model; and the enterprise recruiter determines an intention job seeker according to the interview comprehensive evaluation report, and generates an in-job notification and an in-job guide process.

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 talent cultivation management systems, in particular to an enterprise talent cultivation and management platform based on big data, which constructs a'data perception-portrait construction-intelligent decision-feedback closed loop 'dynamic ecological system, realizes continuous perception and dynamic evaluation of employee ability, and improves the enterprise talent cultivation and management efficiency. The problem of evaluation lag of a traditional culture management platform is solved; the multi-source data acquisition and multi-source data fusion module is matched with the dynamic ability portrait construction and updating module in real time, and evaluation, cultivation and selection of talents become extremely objective and accurate through data-driven ability portraits; prediction and early warning capabilities are provided, so that human resource management is changed from passive response to active planning and intervention; according to the method, the isolated relationship between enterprise talent management and talent cultivation is broken through, various HR data islands are broken through, the situation that cultivation resources are input to employees with high demission risks is avoided, human resource transactional work is greatly reduced, and management efficiency and decision scientificity are improved.

The invention relates to a human resource information management method and device based on LLM + RPA, and the method comprises the following steps: recognizing the abnormality of employee basic information in a human resource system through RPA, marking and generating abnormal marking information; and generating a correction notification template, and forming a notification delivery record by combining batch filling and distribution of employee contact information. And based on the delivery record, intelligently sorting the overdue uncorrected items according to the abnormal level, the overdue day number and the influence range by utilizing LLM, generating an urging sequence, sequentially triggering secondary reminding by RPA, and obtaining an execution result. And finally, the RPA associates and verifies the secondary reminding result and the corrected information, converts the secondary reminding result and the corrected information into a system compatible format, updates the secondary reminding result and the corrected information to a human resource system, and generates an employee information management table, thereby solving the technical problems that a traditional human resource management system still depends on a large amount of manual intervention in the aspect of dynamic update of employee information, so that the management efficiency is low and errors are easy to occur.

The invention discloses a human resource data classification statistical method and system based on big data. The method comprises the following steps: collecting employee basic information and employee behavior data; performing coding processing on the staff statistical data, establishing a staff multi-modal feature set according to the staff basic information and the staff behavior data, inputting the staff multi-modal feature set into a deep learning model, and predicting staff skill scores; extracting the employee behavior data and the employee skill score, constructing an employee behavior feature matrix and a post skill feature matrix, setting a first potential factor and predicting an employee stable value according to the behavior feature matrix, and setting a second potential factor and predicting a post matching value according to the post skill feature matrix; according to the employee stable value and the post matching degree, post recommendation scores are distributed, and a recommendation score thermodynamic density map is visually output; according to the method, the whole process from data acquisition to decision recommendation is automatic, talent evaluation precision is realized, employee demission risks are effectively predicted, and digital transformation of human resource management 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 present invention discloses an enterprise human resources comprehensive management platform, which relates to the field of data management technology and includes: a resource management system determination module for determining a resource management system; a management logic chain determination module for determining a management logic chain; a task management strategy determination module for determining a task management strategy; a sensitive management mode setting module for setting a sensitive management mode for sensitive data classes; a sensitive management strategy determination module for determining a sensitive management strategy; and a pre-management task control module for executing and controlling pre-management tasks. The platform solves the technical problems of the existing enterprise human resources management, such as the difficulty in coping with complex and changing enterprise management needs, the lack of integration of multiple enterprise application systems, and the risks of sensitive data management, which lead to the inaccuracy and security of enterprise human resources management. The platform intelligently realizes the comprehensive integration and efficient use of human resources information, achieving the technical effect of improving the accuracy and security of enterprise management.

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 provides an intelligent salary calculation method and device, electronic equipment and a storage medium, and relates to the field of enterprise human resource management.In the method, a user can flexibly configure a salary formula and automatically carry out salary calculation, intelligence is good, salary strategy simulation (namely salary back-test calculation) is supported, an execution track during formula execution can be displayed, and the method is suitable for popularization and application. And the method has result interpretability.

The invention relates to the technical field of talent development evaluation, and discloses a multi-dimensional data fusion-based intelligent evaluation method for talent development of a power grid company, which is used for solving the problem that an evaluation period is no longer representative during talent development evaluation, and comprises the following steps of: collecting original development data of each person in a human resource management system; the method comprises the following steps: performing standardization processing on original data, constructing a multi-dimensional feature data set, constructing a talent development analysis model, setting an initial evaluation period, obtaining fluctuation data based on the multi-dimensional feature data set, performing evaluation according to the fluctuation data to obtain a period adaptability deviation index, and judging whether the current evaluation period needs to be adjusted or not. If it is judged that the current period needs to be adjusted, the initial evaluation period is adjusted to obtain an actual evaluation period, the accuracy of talent development evaluation is effectively improved, and the credibility of an evaluation result is improved.

The invention discloses a person and post matching method and device, equipment, a storage medium and a program product, and relates to the technical field of human resource management, and the method comprises the steps: obtaining a post specification inputted by a user, and carrying out the analysis and standardization processing of the post specification, and obtaining a processed post specification; matching in a preset candidate database by combining the large model subjected to fine tuning training with a first requirement in the processed post specification to obtain candidate members; and in combination with a second requirement in the post specification after processing, scoring the candidate persons through the large model after fine tuning training to obtain final matching persons. According to the method, personnel are screened according to the first requirement in the processed post specification based on the large model subjected to fine tuning training, and then scoring and sorting are performed according to the second requirement for the screening result, so that more accurate post personnel recommendation is realized, and the accuracy, real-time performance and interpretability of personnel and post matching are improved.

The invention provides an employment public service platform, and relates to the technical field of human resource management, and the platform comprises a demand data storage unit which builds a database of demand professional course information of each post corresponding to each enterprise, according to the market change data, controlling to carry out adaptive adjustment on the course information of each requirement specialty in the database; the satisfaction data calling unit is used for inputting personal verification information of employees participating in the employees and calling out satisfaction professional course information matched with the employees; and the promotion data analysis unit is used for acquiring required post information corresponding to employees. According to the employment public service platform provided by the invention, post matching can be efficiently completed according to learning information mastered by employees and learned information required by enterprise posts.

The invention discloses an Internet-based intelligent human resource management method and system, and relates to the technical field of intelligent human resource management, and the system comprises an automatic recruitment subsystem, a performance management subsystem, an employee service management platform, an intelligent optimization adjustment module, and a personnel data management module. The automatic recruitment subsystem is used for selecting and collecting data information of applicants meeting company post requirements, screening the data information and then automatically arranging interviews, inputting the applicants according to interview results, and arranging corresponding skill training according to personal skill information of the applicants. According to the intelligent human resource management system, datamation and intelligentization of various businesses of human resource management are realized, the operation process is simplified, and the management efficiency is improved; through real-time management of employee information, the employee condition can be mastered more accurately, human resources are reasonably allocated, the overall competitiveness of an enterprise is improved, the diversified requirements of modern enterprises in the aspect of human resource management are met, and the management efficiency and the decision quality are improved.

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 discloses an employee assessment management method and system based on a cloud platform, and particularly relates to the technical field of human resource management.The method comprises the steps that attendance coordinate data, customer evaluation star-level scores and sales order completion quantity are collected in real time through a real-name account system, and a multi-source work data set is generated through abnormal value filtering and sliding window mean value processing; dynamically adjusting the ratio of the customer evaluation weight to the attendance weight, and constructing a five-level achievement step based on extreme value difference equal-ratio division; extracting historical threshold data according to the number of times of achievement unlocking to generate a calibration evaluation benchmark, and verifying and triggering a cross-end game reward instruction in combination with a double-end timestamp difference value; and aligning a re-judgment achievement condition through a timestamp, and sending a virtual asset increment update packet to realize cross-end state synchronization. According to the method, the dynamic adaptive capacity of an evaluation system to service fluctuation is improved, the association accuracy of achievement excitation and work performance is enhanced, the problem of misjudgment caused by asynchronous transmission of data is solved, and the objectivity of an evaluation result and the fault tolerance of the system are ensured.

The embodiment of the invention provides a salary payment and entry method and device, equipment, a storage medium and a program product, and particularly relates to the technical field of salary payment and entry. The method comprises the following steps: controlling a human resource management system to send approved salary data to a financial management system; controlling the financial management system to carry out financial accounting element information supplement on the salary data, generating salary accounting reference data, and sending the salary accounting reference data to the salary management system; and controlling the salary management system to generate a plurality of financial statements based on the salary accounting reference data and a preset financial statement template, and sending at least one financial statement in the plurality of financial statements to a target system in the enterprise terminal and at least one financial statement in the plurality of financial statements to the bank terminal, therefore, salary payment and salary entry are completed. The method is used for achieving the effect of improving the efficiency and accuracy of salary payment and entry.

The invention discloses a human resource management information integration method based on a block chain, and the method comprises the steps: collecting human resource information, and carrying out the dynamic structural processing of the human resource information, and obtaining a structural data set; dividing the data into a plurality of data fragments, and encrypting the plurality of data fragments by using an inner product function encryption algorithm to obtain encrypted data fragments; storing the data in an alliance block chain network; generating an autonomous identity identifier for each user, binding the autonomous identity identifier of the user with a cryptographic key thereof, and storing the autonomous identity identifier in an alliance block chain; when the user requests to access the encrypted data fragment, verifying the verifiable certificate and authority of the user through an intelligent contract mechanism; in an encryption state, directly performing homomorphic calculation on the processed data fragments to obtain an analysis result; and the public key of the target receiver is used to encrypt the analysis result to obtain an encrypted analysis result, the encrypted analysis result is stored on the alliance block chain and is distributed to the authorized user, and the authorized user decrypts the result through the private key.

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.