259 results about "Skill sets" patented technology

The invention discloses an employment information matching method and system based on data analysis, and particularly relates to the field of employment matching, and the method comprises the steps: collecting structured and unstructured data, and carrying out the semantic feature extraction through employing a BERT model and BiLSTM-CRF; in the preprocessing stage, entity standardization is realized through a knowledge graph, and a job seeker portrait and post model including a skill matrix and an occupational development trajectory is constructed; in the feature engineering stage, extracting four core features of skill matching degree, salary expectation integrating degree, commuting tolerance and occupational development goodness of fit; the salary integrating degree is quantitatively evaluated through a bidirectional tolerance model, a random forest model with time decay is used for dynamic weight, feature weight is generated based on historical successful cases, and a real-time feedback mechanism is introduced to adjust a weight coefficient; finally, the matching degree function fuses the weighted features and the industry trend factors, and the model is continuously optimized through a three-level updating mechanism.

The embodiment of the invention provides an intelligent learning path recommendation method and system based on a dynamic state. The method is applied to the technical field of intelligent learning recommendation, and comprises the following steps: calculating a skill adaptation weight, a load weight and an emergency degree weight in real time based on a dynamic state of a target employee, including a current skill improvement condition, a workload and a task emergency degree; combining the skill matching degree, the learning strength and the task association degree of each learning unit in the candidate learning path, and performing comprehensive evaluation by using a multi-weight scoring function; and sorting the paths according to the comprehensive score, generating a personalized recommended learning path set and sending the personalized recommended learning path set to an employee terminal, thereby realizing intelligent learning path recommendation with dynamic adaptation and accurate matching. According to the scheme, personalized learning path pushing aiming at actual post requirements and working states of the employees can be realized, correlation, urgency and acceptability of learning contents are improved, learning efficiency and task adaptability are remarkably enhanced, and the employees are helped to quickly compete with post targets.

The invention discloses a multi-intention control method and device based on a large model, a storage medium and an electronic device, and relates to the technical field of smart home, and the method comprises the steps: carrying out the intention recognition of a voice instruction corresponding to a target object, so as to determine a plurality of to-be-executed intentions indicated by the voice instruction; each to-be-executed intention is input into a preset large language model, so that the preset large language model extracts a keyword corresponding to each to-be-executed intention, the intention type corresponding to each to-be-executed intention is recognized according to the keyword corresponding to each to-be-executed intention, and the intention type comprises an equipment control type intention and a skill type intention; the conversion mode of each to-be-executed intention is determined according to the intention type, and each to-be-executed intention is converted into each target instruction according to the conversion mode, so that each target to-be-executed device executes each target instruction, and the target instructions at least comprise one of a control type instruction and a skill type instruction.

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.

The invention discloses a personalized intelligent interview system, and relates to the technical field of artificial intelligence and recruitment interview, and the system comprises a position information analysis module which is used for inputting an original position description text, carrying out the analysis through employing a natural language processing NLP technology, and extracting structured position demand data containing skill items, characteristic items and quantification levels; the resume / position intelligent matching module is used for receiving the structured position demand data, receiving a job seeker resume text, performing intelligent matching analysis by constructing a skill semantic vector space, and outputting a multi-dimensional matching score matrix and an investigation key index set; according to the job demand and the job seeker resume, personalized interview topic screening and optimization are realized, and the interview pertinence and accuracy are improved; the job seeker is comprehensively evaluated, and the resume / position matching information is combined, so that a more comprehensive evaluation and scoring basis is provided, and an enterprise is helped to make a more accurate recruitment decision.

Various embodiments set forth a techniques for generating computer-aided design (CAD) models that includes receiving a plurality of inputs via a user interface, generating a plurality of geometric prompts based on the plurality of inputs, executing a trained machine-learning model on the geometric prompts to generate CAD data, and generating at least one CAD model based on the CAD data. Advantageously, the disclosed techniques can substantially facilitate the overall process of designing CAD objects and CAD models of differing levels of complexity, thereby increasing the accessibility of CAD software and applications to a wider array of users with differing skill sets.

The invention provides a post recommendation method and system based on resume analysis, and relates to the technical field of big data analysis, and the method comprises the steps: obtaining resume data of a job seeker; performing natural language processing on the resume data to obtain a plurality of keywords, wherein the keywords comprise skill keywords and job application intention keywords; determining the job application field of the job seeker; performing prediction to obtain future market recruitment information and future market demands; a dynamic market label is generated; determining an expected matching degree according to the skill keyword and the job-hunting intention keyword in combination with a dynamic market tag; and according to the expected matching degree of each post, generating a post recommendation strategy of the job seeker. According to the method, the expected matching degree is calculated in a three-dimensional mode through skill keywords, job hunting intention keywords and dynamic market tags, the defects that a traditional method neglects tag semantic association and only depends on static data are effectively overcome, and the man-post matching accuracy is remarkably improved.

The invention relates to a skill grade evaluation method and system for talent management. The skill grade evaluation method comprises the steps of obtaining target occupational information, corresponding occupational element information and assessment index information; constructing a multi-channel evaluation model based on the occupational element information and the assessment index information; obtaining target skill data and performing preliminary evaluation to generate a standardized evaluation result; obtaining target historical behavior data and extracting skill mode features and implicit capability features; inputting the skill mode features and the implicit capability features into a multi-channel evaluation model to generate a personalized evaluation result; in conclusion, according to the skill grade evaluation method and system for talent management provided by the invention, standardized evaluation is carried out on skill data by constructing a multi-channel evaluation model, and dynamic correction is carried out in combination with implicit features extracted from historical behavior data; the method has the advantages of dynamically capturing skill demand changes, identifying skill synergistic effects, mining recessive ability characteristics and providing timeliness occupational planning.

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.

Various embodiments set forth a techniques for generating computer-aided design (CAD) models that includes receiving a plurality of inputs via a user interface, generating a plurality of geometric prompts based on the plurality of inputs, executing a trained machine-learning model on the geometric prompts to generate CAD data, and generating at least one CAD model based on the CAD data. Advantageously, the disclosed techniques can substantially facilitate the overall process of designing CAD objects and CAD models of differing levels of complexity, thereby increasing the accessibility of CAD software and applications to a wider array of users with differing skill sets.

The invention relates to the technical field of occupational skill evaluation, and particularly discloses an online evaluation system and method based on occupational skills, and the system comprises the steps: building a multi-task learning framework comprising a shared feature extraction module and a task exclusive head through collecting the multi-modal behavior data of a user in the process of executing an occupational skill task; jointly training a plurality of related tasks to improve the generalization ability of the model; a pre-training teacher model is introduced, cross-domain knowledge is migrated through a knowledge distillation mechanism, and lightweight student model performance is optimized in combination with a regularization strategy; calculating a cognitive load fluctuation characteristic value and a skill migration consistency characteristic value based on student model output, and fusing to generate a composite risk assessment vector; an asynchronous parallel optimization model is input for comprehensive evaluation, and a structured evaluation report and personalized comments are output in combination with an SHAP interpretability analysis and natural language generation module.

Embodiments are directed to managing data for skill extraction pipeline. Skill spans may be determined based on skill information associated with job descriptions such that each skill span includes words included in the skill information. A comparison of the skill spans with other skill spans associated with a skill knowledge graph may be generated. Skill nodes may be generated for the unmatched skill spans. The new skill nodes may be integrated into the skill knowledge graph. Accordingly, the skill graph may be automatically updated for use in job / career applications including report generation.

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.

One embodiment provides a method, the method including: identifying, using a task guidance system, a task to be performed by a user; determining, using the task guidance system, a skill level of the user with respect to the task, wherein the determining includes accessing a profile of the user identifying a plurality of tasks and a skill level of the user for each of the plurality of tasks; and providing, to the user and using the task guidance system, an instruction set for performing the task, wherein a level of detail within the instruction set provided is based upon the skill level of the user. Other aspects are claimed and described.

Certain aspects of the present disclosure provide techniques for providing job skill recommendations for an electronic document. Certain aspects include obtaining work history statements, a current job title, and an experience level, querying curated skills datasets to return a first skill set, generating, with an artificial intelligence model, work history embeddings based on the work history statements, generating, with the artificial intelligence model, skill embeddings based on the curated skills datasets, determining a similarity score between the work history embeddings and the skill embeddings, selecting, for a second skill set, second job skills, identifying common skills between the first skill set and the second skill set, merging the first skill set and the second skill set to form a merged skill set, sorting the merged skill set into an ordered list and populating sections of the electronic document by selecting at least one skill from the ordered list.

The invention discloses an enterprise human resource intelligent recruitment and talent management system, and relates to the technical field of enterprise recruitment and management. A BERT model is adopted for word segmentation, 12 types of key indexes are extracted, self-defined weights are supported, position portraits containing 6-8 core requirements are generated, resumes are converted into 300-dimensional vectors, the matching degree with the portraits is calculated, missing items are marked, and the resumes are repeatedly delivered within 30 days after shielding. Generating a comprehensive score of 0-100 points through an AI interview robot from three-dimensional evaluation of professional ability, comprehensive quality and culture matching degree; storing candidates according to six categories, generating 5-7 skill labels, and automatically pushing position updating; recording performance, training and promotion data, generating a growth curve, and predicting a promotion post; 15 indexes are counted, a visual report is generated, and improvement suggestions are triggered. The recruitment efficiency and precision are improved, talent management scientificity is enhanced, a data decision closed loop is formed, team stability is improved, and enterprise development is guaranteed.

The invention discloses a labor capability allocation method and device based on a dynamic weight, a medium and a product, and the method comprises the steps: obtaining the complexity and personnel skill data of each task in response to a project labor capability allocation request; based on the dynamic coupling model, calculating the real-time matching degree of the personnel and the tasks in combination with the dynamic weight factors corresponding to the tasks; then, according to a matching result and multi-dimensional constraints such as project cost and time, a multi-objective optimization algorithm is adopted to generate an optimal labor force and energy distribution scheme and expected progress data; after the scheme is executed, the actual progress of the project is monitored in real time and compared with expected data; if the deviation exceeds a set threshold value, a feedback mechanism is triggered, the personnel skill data and the dynamic weight factor are updated, the matching and optimizing process is restarted, and closed-loop self-adaptive management of the whole period of the project is achieved until the project is completed, and the technical scheme of the embodiment of the invention remarkably improves the accuracy of resource allocation and the self-adaptive capacity of project management.

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.

To provide a job search support system, etc. for supporting job seekers in inputting information.SOLUTION: There is provided a job search support system for job seekers. The job search support system includes at least one processor. The processor is configured to read a program to execute the following steps: a receiving step of receiving a job history of a job seeker, which is generated or updated according to input by the job seeker, the job history including job details corresponding to at least one organization to which the job seeker belongs; and a presenting step of presenting at least one skill tag to the job seeker in response to execution of the receiving step, where the skill tag is extracted on the basis of the job history, is related to skills or experience of the job seeker, and when the job seeker selects a skill tag, the skill tag is associated with the job seeker as skill information of the job seeker.SELECTED DRAWING: Figure 1

Systems and methods described herein provide for identifying a skillset to augment in a learner agent system; selecting, from a pool of candidate instructor agent systems associated with a multiagent training platform, one or more instructor agent systems based on instructor skills documentation data descriptive of respective skill capabilities of the candidate instructor agent systems; obtaining at least one training task representative of the skillset; generating a learner solution to the at least one training task using the learner agent system; generating instructor feedback data using the one or more instructor agent systems and the at least one training task, the instructor feedback data descriptive of a qualify of the learner solution; and training the learner agent system based on the instructor feedback data.

To provide a technique capable of electronically recording skills efficiently.SOLUTION: A skill transfer support system includes: a motion extraction unit that extracts one or multiple motions of a worker; an action list generator that generates a captured operation list including the motions extracted by the motion extraction unit; an actual work video acquisition unit that acquires actual work video; and an actual work video determination unit that determines whether the operation included in the captured operation list is captured in the actual operation video.SELECTED DRAWING: Figure 1

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 invention is suitable for the technical field of post matching, and provides a multi-dimensional intelligent matching method and system for employment posts, and the method comprises the following steps: carrying out the comprehensive skill matching of posts and talents, and determining a comprehensive skill matching score; calling educational background information and certificate information in the talent resume, and reasoning to determine the learning ability of the talent; extracting post skills which are matched unsuccessfully in the employment posts, determining the demand emergency degree and learning difficulty of each post skill which is matched unsuccessfully, and determining the association degree between the post skills and talent skills and the association degree between the post skills and professions; and based on the learning ability, the demand emergency degree, the learning difficulty and the correlation degree, determining the cultivation cost cardinal number of each post skill which fails in matching. According to the invention, the learning ability of talents is incorporated into a matching evaluation system, so that potential suitable talents with relatively strong learning ability and development potential although the current skills are not completely matched with posts can be identified, the talent selection range is expanded for enterprises, and the talent recruitment efficiency 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.