179 results about "Skill sets" patented technology

The invention discloses an industry post skill intelligent evaluation method and system based on an AI knowledge graph, and relates to the technical field of post skill data processing. The industry post skill intelligent evaluation method and system based on the AI knowledge graph comprises the following steps: S1, acquiring post skill graph data, and preprocessing the post skill graph data; s2, generating candidate post skill connection edges, evaluating post skill map data credibility, and constructing an effective post skill node set; s3, constructing a local post skill subgraph, removing abnormal connecting edges, performing post skill consistency evaluation on the remaining connecting edges, and implementing a hierarchical connecting edge input strategy; and S4, executing post skill map version updating, evaluating the evolutionary stability of the map, and implementing hierarchical updating control. The problem that according to an existing post skill knowledge graph, due to abbreviation of terms during post information filling, information scarcity, mistaken linking and low-quality connected-edge writing are caused, and therefore the reliability and stability of the graph are reduced is solved.

A dialogue system, comprising:an input, configured to receive input data from a user, wherein the input data comprises one or more of text data, speech data, image data and motion data; an output, configured to output data to the user; and one or more processors, configured to:obtain information identifying a skill and obtain information identifying a proficiency level of the user for the identified skill from stored proficiency level information; and execute at least one iteration of a coaching session, each iteration comprising performing one or more dialogue interactions, wherein each dialogue interaction comprises:receiving first input data from the user via the input;generating a first language model prompt and providing the first language model prompt to a language model, said first language model prompt comprising the first input data, the information identifying a skill, the information identifying a proficiency level of the user for the identified skill and a request to generate coaching information based on the first input data, the information identifying a skill and the information identifying a proficiency level; and generating first output data based on a first language model response to the first language model prompt and outputting, via the output, the first output data to the user;wherein the at least one iteration of the coaching session further comprises, after the one or more dialogue interactions:generating a second language model prompt and providing the second language model prompt to the language model, said second language model prompt comprising the information identifying a skill, the information identifying a proficiency level of the user for the identified skill, the first input data and the first output data, and a request to generate at least one proficiency update assessment based on the first input data, the first output data, the identified skill and the information identifying a proficiency level; generating second output data based on a second language model response to the second language model prompt and outputting, via the output, the second output data to the user; receiving second input data from the user via the input; determining a revised proficiency level of the user for the identified skill based on the second input data; andupdating the stored proficiency level information based on the revised proficiency level.

The invention discloses an operation automation generation method and device and a storage medium, and relates to the technical field of automatic operation, and discloses an operation automation generation method, which comprises the following steps: generating a skill model based on an operation behavior sequence of a user in a business system, the skill model comprising a plurality of atomic operations, the execution condition and the sequence dependency relationship of the atomic operation are determined; in response to the automatic execution request, obtaining a current interface of the target service system, and comparing the current interface with a historical interface associated with the corresponding atomic operation in the skill model; according to a comparison result, performing adaptive adjustment on the corresponding atomic operation in the skill model to obtain an adjusted skill model; and based on the adjusted skill model, executing automatic operation in the target business system. Through an adaptive adjustment mechanism, the automatic process can dynamically adapt to the interface change of the target business system, and the maintainability of cross-system operation automation is effectively improved.

A method for performing a dialog session including receiving a user input from a chatbot application wherein the user input is indicative of a user intent associated with one of a plurality of skills, generating an input vector in response to the user input, generating a list of skills in response to a semantic search comparing the input vector to a plurality of skills vectors where each of the plurality of skills vectors is associated with one of the plurality of skills with the vector to determine a list of skills matching the vector, identifying an intended skill from the list of skills in response to the list of skills and the input vector using a large language model, and performing the intended skill in response to the identification of the intended skill.

The present invention provides a user management device that allows for more appropriate information provision to users compared to managing users according to their roles. [Solution] The management device is characterized by comprising a management means for managing users by a first management method for managing the level of users who use the molding device according to their roles, and a second management method for managing the level of users according to their skill level in the work.

The invention, which relates to the technical field of job application data management, discloses a job seeker portrait construction and post intelligent matching system comprising a portrait construction module, a skill analysis module, an extension module, a team analysis module, and a post intelligent matching module. According to the invention, real-time job seeker dynamic data is obtained through an online job hunting platform, dynamic fluctuation high-frequency skills and confidence coefficients are identified and labeled, skill feature data and occupational tendency offset feature data are extracted, and a core skill decline rate and an occupational path offset index are calculated respectively; the skill learning time is analyzed to generate the skill learning degree of the job seeker, the skill obtaining speed and ability of the job seeker can be reflected, the integrating degree of a job seeker expectation model is evaluated, a comprehensive matching score is generated through fusion, the requirement of a team for the job seeker is concerned, the expectation and satisfaction of the job seeker are also considered, and the experience of the job seeker is improved. And intelligently recommending a post list with the highest comprehensive matching score to the job seeker based on the comprehensive matching score of the job seeker.

This invention belongs to the field of intelligent scheduling technology in manufacturing, and particularly relates to a dual-resource flexible job shop scheduling method and system integrating a large language model and deep reinforcement learning. The method includes: constructing a dual-resource flexible job shop scheduling environment model, defining jobs, processes, machines, workers, and their constraints, and constructing a set of state features for reinforcement learning; designing an action space and feasible action masking mechanism, based on process sequence, feasible machine set, worker skill qualifications, and available time constraints, to mask infeasible actions and reduce the probability of selecting low-quality actions; designing a multi-objective reward function, including minimizing completion time and total energy consumption; training the scheduling strategy using the Asynchronous Advantage Actor-Critic (A3C) algorithm, optimizing the policy network and value network through multi-threaded parallel sampling and asynchronous update mechanisms; and triggering the large language model to generate new reinforcement learning definitions based on trend and stability analysis of training feedback, and achieving adaptive iterative optimization through a closed-loop mechanism.

A system is provided.SOLUTION: A system comprising: means for collecting email data of employees; means for collecting chat data of employees; means for collecting documents created by employees; means for analyzing the collected email data, chat data, and documents to extract keywords and phrases; means for classifying the extracted keywords and phrases to identify skill sets and work contents of employees; means for registering the identified skill sets and work contents in a database for each employee; and means for reflecting the registered skill sets and work contents in a visualization tool.SELECTED DRAWING: Figure 1

The invention relates to the technical field of information processing, in particular to a person and post matching method, device and equipment based on skill verification and a storage medium. An initial user portrait is constructed according to resume information, and the skill field and skill level are determined based on self-described core skills and self-described skill proficiency; and dynamically generating a test question set matched with the skill field and the skill level, collecting answer results after the user completes the test question set, introducing skill verification to improve authenticity, calculating skill level parameters of each skill of the user by using a preset project reaction theoretical model, and calculating the skill level parameters of each skill of the user. The initial user portrait is dynamically corrected according to the skill level parameters, so that the skill mastering degree can be hierarchically defined and dynamically adjusted, the potential promotion space and development potential of the user can be found, and the final user portrait is matched with the post knowledge graph to improve the user experience. And a post recommendation list is generated according to the matching result, and a skill gap analysis report is output, so that the post matching accuracy is improved.

The application relates to the technical field of artificial intelligence, in particular to a multi-skill fusion method and device based on a professional knowledge base, equipment and a storage medium, which comprises the following steps: receiving a target task and calling a global professional knowledge base, the knowledge base storing task decomposition rules, skill dependency relationships and conflict resolution rules; analyzing the target task into multiple ordered subtasks according to the task decomposition rules; sequentially selecting a matching target skill from a skill pool according to the skill dependency relationship for each subtask and calling execution to obtain an original execution result; when multiple mutually conflicting original execution results of the same subtask are obtained, the conflict resolution rules are used for judgment to obtain a final execution result; and finally, the final execution results of all the subtasks are summarized to generate the overall output of the target task. The global knowledge base is used for unified guidance of task decomposition, skill selection and conflict resolution, and the reliability and dynamic adaptability of multi-skill fusion are improved.

The present application relates to the technical field of computer, in particular to a kind of experience-based field technician scheduling method and system, method includes: obtaining scheduling input data, including the directed graph of node and task node, travel time, available technician set, skill domain information, proficiency level, skill domain demand and demand proficiency level, income, task time window, work time window, service duration mapping relationship;According to proficiency level and demand proficiency level, compatible relationship is generated and experience-related service duration is calculated;Under the feasibility constraint, scheduling scheme is constructed, task node unique allocation is satisfied, job route is started from node and returns node, service starting time is determined according to travel time and experience-related service duration to satisfy time window;Heuristic insertion generates initial scheduling scheme;Iterative local search generates neighborhood, temperature parameter probability acceptance, disturbance and cooling;The optimal scheduling scheme is output to maximize the income.The present application can solve the problem of inaccurate time consumption estimation and insufficient plan robustness caused by the fact that the experience / proficiency of technicians is not explicitly reflected in the existing field technician scheduling.

We provide the system. [Solution] A means of entering candidate information, A means of analyzing the entered candidate information to identify the candidate's skill set and career path, A means for generating customized interview questions based on analyzed information, A method for generating a follow-up email to send after the interview, A means of collecting feedback from interviewers and updating the interviewer training program, A system that includes this.

The present disclosure provides a turn-based game operation control method and device, electronic equipment and storage medium, the method comprising: displaying a skill operation panel in a first area of a graphical user interface within a turn of a target character of a first party, the skill operation panel containing at least one skill control corresponding to the target character of the first party; in response to a first touch operation on the skill control, displaying a character unit identifier of a candidate target corresponding to a skill type of the skill corresponding to the skill control in a second area of the skill operation panel; in response to a drag operation continuous with the first touch operation, determining a selected action object according to a relative positional relationship between a current position of a touch point of the drag operation in the second area and the character unit identifier; and in response to an end of the drag operation, determining the selected action object as a to-be-released target of the skill. This helps to reduce operation steps and drag distance, and improves the accuracy of target selection.

The present disclosure generally relates to determining a do-it-yourself (DIY) skill level, and / or determining if home improvement projects should be completed via a DIY technique or via hiring a professional. In some embodiments, one or more processors: receive answers to a set of questions; determine a DIY score based upon the answers; receive a home improvement project for the home and a difficulty score of the home improvement project; determine, based upon the DIY score and the difficulty score of the home improvement project, a recommendation to complete the home improvement project via a DIY technique; and / or cause a display to display the recommendation to complete the home improvement project via the DIY technique.

This application relates to a method, system, device, and medium for personalized vocational skills learning path planning based on artificial intelligence. The method includes: collecting a user's structured event dataset; constructing a dynamic causal skill graph with skill points as nodes and causal effect strength as directed edges using two-stage linear regression; extracting the user's dynamic behavior sequence and inputting it into a pre-trained model to obtain a skill mastery vector; searching for a personalized causal learning path with the current mastered skill points as the starting point, the career goal as the ending point, and maximizing the cumulative causal effect as the objective; performing counterfactual reasoning on the learning path based on the structured causal model to predict the counterfactual mastery, learning time, and path under different intervention conditions; and obtaining the optimal learning path adjustment scheme by weighted fusion of the counterfactual results. This method enables personalized learning path planning and dynamic optimization with causal logic.

We provide the system. [Solution] An input method for entering individual skills information of job seekers, An analysis means that analyzes the skill information input by the input means and generates a skill profile, An information selection means for selecting job postings based on the skill profile generated by the aforementioned analysis means, A means for displaying job information selected by the aforementioned information selection means to the user, A content generation means that generates learning content based on the skills that are lacking, Means for providing the user with the learning content generated by the content generation means, A system that includes this.

The application relates to a talent matching and intelligent recruitment method and system based on an AI large model, which comprises the following steps: acquiring multi-modal data of candidates and post demand data of a recruitment party; performing semantic extraction and feature fusion on the multi-modal data through a multi-modal fusion encoder to generate a comprehensive feature vector containing semantic correlation features and behavior features; performing field adaptation processing on the comprehensive feature vector based on a dynamically updated industry knowledge graph to generate a skill label set of the candidates; adopting a reinforcement learning model to calculate the dynamic matching degree of the skill label set and the post demand data according to historical recruitment feedback data to generate a recommendation list; and outputting the recommendation list to a terminal of the recruitment party and online optimizing the reinforcement learning model based on operation behavior data of the recruitment party. The application realizes intelligent matching of job seekers and recruitment requirements, and improves the efficiency and accuracy of recruitment.

The invention relates to the technical field of post recommendation, and particularly discloses a vocational ability dynamic portrait and post recommendation method and system. The method comprises the steps of firstly collecting static data (work resumes, assessment scores and the like) and dynamic behavior data (project tasks, skill training and the like) of a user, laying a comprehensive data source foundation, then disassembling the work resumes, extracting and clustering multiple types of entities, screening and determining a core capability field label in combination with time, secondly quantifying core capability scores and a performance stability coefficient, and finally obtaining a core capability model. Then analyzing dynamic behavior data, extracting evolution characteristics, constructing dynamic capability evolution vectors, fusing the dynamic capability evolution vectors with the static vectors to form vocational capability dynamic portraits, analyzing post demand data, extracting capability requirements and environment characteristics, quantifying the post demand data and the capability requirements and environment characteristics, and carrying out model processing to generate post portrait vectors; and finally, comprehensive suitability is calculated through the cosine similarity and the growth trend matching degree, candidate posts are sorted and recommended, and the integrating degree of the posts and talents is effectively improved.

The invention discloses a test question generation method based on category skill dimensions. The test question generation method comprises the steps of calculating subjective weights and objective weights of multiple skill dimensions; determining a comprehensive weight of the plurality of skill dimensions according to the subjective weight and the objective weight; calculating the matching priority of the scene template test questions; screening a preset number of initial test questions to obtain an initial test question set of multiple skill dimensions; a coverage degree verification step; supplementing the initial test question set according to the test question coverage and the matching priority; and performing test question duplicate removal according to the similarity of the test questions in the supplemented initial test question set to obtain a target test question set. According to the method and the system, test question matching is performed on examination of entering personnel through skills of multiple dimensions in combination with the static dimension and the dynamic dimension, so that the comprehensiveness and scientificity of an evaluation result are improved, skill evaluation is more stereoscopic and objective, and the actual working efficiency of service personnel can be reflected more truly. The invention further discloses a system for implementing the method, electronic equipment and a storage medium.

A system is provided.SOLUTION: A system comprising: means for receiving deal information sent by a trader; generative AI model means for analyzing the deal information and extracting a required skill set; means for searching a database for a freelance having the required skill set; means for selecting an optimal freelance from a result of the searching and notifying the optimal freelance as a matching candidate; and means for receiving an intention of the freelance to approve the matching candidate.SELECTED DRAWING: Figure 1

A system according to an embodiment aims to generate a personalized learning policy based on a skill set of a user and manage learning progress.SOLUTION: A system according to an embodiment includes an initial skill set diagnosis unit, a learning policy generation unit, a question answering unit, a progress management unit, an achievement test unit, and a progress determination unit. The initial skill set diagnosis unit diagnoses an initial skill set of the user. The learning policy generation unit generates a learning policy and a menu based on a result of the diagnosis by the initial skill set diagnosis unit. The question answering unit answers a question during learning in an interactive manner. The progress management unit manages the learning progress of the user. The progress test unit performs a progress test. The progress determination unit determines whether to proceed to the next learning stage based on the test result.SELECTED DRAWING: Figure 1

The system according to this embodiment aims to quantify employees' skills and effectively formulate career plans and learning plans. [Solution] The system according to the embodiment comprises a data collection unit, an analysis unit, a quantification unit, a career plan generation unit, and a learning plan generation unit. The data collection unit collects data on employees' skills. The analysis unit analyzes the data collected by the data collection unit. The quantification unit quantifies skills based on the data analyzed by the analysis unit. The career plan generation unit generates a career plan based on the skills quantified by the quantification unit. The learning plan generation unit generates a learning plan based on the skills quantified by the quantification unit.

The application relates to the technical field of talent evaluation, and discloses a multi-dimensional adaptive examination generation method and system based on a dynamic skill map. The method comprises the following steps: real-time analysis of recruitment website and enterprise job description data, extraction of atomized skill phrases containing skill names, levels and correlation degrees, and generation of unified semantic representation; obtaining a standardized skill map through a large language model and transmitting the standardized skill map to a central database through a blockchain; generating an evolution strategy based on skill node weights and user historical answering characteristics, and differentiating and executing the evolution strategy by edge nodes; selecting a target edge node and configuring a skill knowledge cache; analyzing a candidate natural language answering request to generate ability matching characteristics, determining a candidate test question set, and outputting a test paper; and updating an ability evaluation model and an evolution strategy in combination with an answering result and a response time. The application can improve the authority and reliability of the evaluation result to meet the scientific and accurate needs of enterprises for talent evaluation.

A dynamic career guidance system including a database storing modular career pathways defined by a set of skills and competencies, a user profile management module to track a user's acquired skills and suggest potential career transitions, a real-time data integration module to pull data from external labor market sources such as publicly available labor databases and dynamically update the career pathways based on current trends, and a gap analysis engine to compare a user's current skill set to desired career roles and suggest educational or certification pathways to fill the gaps. The user profile management module continuously updates to reflect new skills acquired by the. The modular career pathways allow users to transition between careers across different industries by identifying transferable skills. The system includes a dynamic visualization tool to present users with potential future career paths, lateral transitions, and progression maps based on their current and target skills.

The subject technology receives an online request from a first player to enter a game via a network. The subject technology determines a set of interoperable skill metrics of the first player, each interoperable skill metric corresponding to a different skill metric. The subject technology selects a particular interoperable metric from the set of interoperable skill metrics based on an analysis of prior game data of the game and an indication of a predictive performance of each interoperable skill metric. The subject technology performs a skill-based matchmaking process to match the first player to at least a second player based at least in part on the selected particular interoperable metric. The subject technology initiates an instance of the game for the first player and the second player.

This invention discloses a transparent and trustworthy method for achieving skill work results based on DLF (Device Flow Framework), comprising the following steps: constructing a vertical model dataset classification system and skill metadata templates, and predefining OFD (Obstacle Course Function) electronic credential templates; recording operational behaviors in real time during skill execution; mapping the recorded information to the corresponding OFD templates to generate a trustworthy OFD electronic credential for a single skill result; generating a DLF trustworthy credential set and a DLF visual call overview diagram for multi-step skill chains; and binding the DLF trustworthy credentials with the vertical model results to achieve bidirectional full-link traceability. This invention constructs a trustworthy electronic credential mechanism for the entire process of skill call. It ensures that each skill call obtains a unique, tamper-proof, and trustworthy identity, fundamentally solving the problems of unclear sources and untraceable processes in skill work results.

The present invention relates to a computer-implemented method for creating a skills graph. Furthermore, the present invention relates to computer-implemented methods for creating a skills profile, generating recommendations, determining differential skills, and more, based on the skills graph. The present invention also relates to a corresponding computer-readable medium and system.In particular, the procedure for creating a skills graph comprises the following steps: a) processing at least one input document to generate a list of skill topic candidates; b) generating a list of skill topics based on the list of skill topic candidates; c) calculating a skill relation value for each pair of skill topics; d) generating a variety of skill labels associated with at least some of the skill topics, in particular using the at least one input document and / or a knowledge base; e) calculating a label association value for each skill label; f) creating a skills graph based on the skill topics, the skill labels, the skill relation value, and the label association value.

The invention discloses a labor education interactive teaching system, belongs to the technical field of education, and aims to solve the problems of rigid evaluation and non-personalized guidance of traditional labor skill training. The system comprises a multi-modal data acquisition module, a baseline management module, a contradiction analysis module, a strategy generation module and a multi-modal interaction terminal module. According to the method, a personal dynamic ability baseline is established, an operation-state contradiction is diagnosed based on deep coupling of real-time behavior data and physiological data, and a composite guidance strategy containing body relaxation guidance or step-by-step technology guidance can be generated in a targeted manner. According to the system, visual, auditory and tactile feedbacks are output in real time through the multi-mode interaction terminal, and the accuracy of labor skill teaching, the fairness of evaluation and the skill generalization ability of a learner in a high-voltage situation are remarkably improved.

An object of a system according to an embodiment is to enable even a user unfamiliar with cooking to find a menu suitable for his / her skill level and improve his / her skill.SOLUTION: A system includes a skill evaluation part, a menu proposal part, and a guide provision part. The skill evaluation unit evaluates the cooking skill of the user. The menu proposal part proposes a menu corresponding to the skill level evaluated by the skill evaluation part. A guide providing part provides a step-by-step guide for skill improvement on the basis of the menu proposed by the menu proposal part.SELECTED DRAWING: Figure 1