15 results about "Recruitment methods" patented technology

The invention relates to a talent matching and intelligent recruitment method and system based on an AI large model. The method comprises the steps of obtaining multi-modal data of candidates and post demand data of recruiters; 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 association 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 candidates; performing dynamic matching degree calculation on the skill label set and post demand data according to historical recruitment feedback data by adopting a reinforcement learning model to generate a recommendation list; and outputting the recommendation list to a recruiter terminal, and performing online optimization on the reinforcement learning model based on operation behavior data of a recruiter. According to the invention, intelligent matching of the job seeker and the recruitment demand is realized, and the recruitment efficiency and accuracy are improved.

The invention discloses a one-stop intelligent recruitment method, device and equipment and a storage medium, and the method comprises the steps: analyzing an electronic resume uploaded by a user, and extracting personal basic information; pushing an online evaluation questionnaire to the user, obtaining evaluation result data of the user, and performing dimension alignment on the personal basic information and the evaluation result data to generate a user comprehensive information file; acquiring post demand data corresponding to a preset job fair, analyzing the post demand data, and generating post feature vectors; constructing a matching model corresponding to the user and the post based on a deep matching neural network, inputting the user comprehensive information file and the post feature vector into the matching model, and outputting a candidate post list containing a matching degree score; receiving a target post selected by the user from the candidate post list, constructing an AI virtual interview scene, and analyzing the answer content of the user in the virtual interview to generate an interview evaluation report; and analyzing the interview evaluation report to assist the user in participating in the preset recruitment fair.

The invention discloses an automatic intelligent recruitment method, system and device and a medium. The automatic intelligent recruitment method comprises the steps of autonomously performing interactive guidance with an enterprise when the enterprise has a recruitment demand so as to actively guide the enterprise to perfect recruitment information and obtain real enterprise terminal information of the enterprise; when an applicant has an application demand, interactive guidance with the applicant is autonomously carried out, so that the applicant is actively guided to perfect a resume and the application demand, and real comprehensive information of the applicant is obtained; and according to the accurate recruitment information of the enterprise, the enterprise terminal information, the accurate resume of the applicant, the job application demand and the comprehensive information, the enterprise and the applicant are matched, and an accurate matching result is obtained. By adopting the method and the device, personnel work such as resume searching, screening and matching before offline interview can be automatically completed, accurate two-way matching of an enterprise and an applicant is realized, respective screening work of the enterprise and the applicant is saved, and then the recruitment efficiency, the recruitment quality and the recruitment satisfaction degree are improved.

A method of performing automated job recruitment includes receiving a plurality of recruitment listings, each including data indicative of job qualifications. The method includes compiling a body of knowledge based on the recruitment listings, and receiving a job application from a candidate, which includes a resume and a target recruitment listing. The method includes extracting relevant data from the resume and providing the job application to a hiring entity corresponding to the target recruitment listing. Upon providing the job application to the hiring entity, the method includes providing the candidate with an automated status update response indicating that the candidate is being considered for the target recruitment listing. The method includes receiving an acceptance / rejection communication from the hiring entity, indicating whether the candidate has been accepted or rejected for the target recruitment listing, and providing another automated response to the candidate indicating whether the candidate has been accepted or rejected.

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 provides a building worker recruitment method and system, and relates to the technical field of data processing. The method comprises the following steps: acquiring application information of an applicant; determining one or more reference workers based on the target post and / or resume information; and based on the historical rectification information of the one or more reference workers, determining the assessment content of the applicant. The system comprises an acquisition module used for acquiring application information of applicants; the first determination module is used for determining one or more reference workers based on the target post and / or resume information; and the second determination module is used for determining the assessment content of the applicant based on the historical rectification information of the one or more reference workers. According to the invention, enterprise own data and external data can be fully utilized to formulate recruitment assessment content more suitable for enterprise management styles or special scenes, and the assessment result of the recruitment process is utilized to customize targeted training content for recruitment personnel.

We will flexibly recruit workers for a single job posting. [Solution] The recruitment system described herein generates multiple job postings that include job descriptions and recruitment slots, with at least a portion of the job descriptions being common to all of them, and accepts applications for these multiple job postings. When predetermined conditions are met, the recruitment system adds at least a portion of the difference between the recruitment slots and the number of applicants for the first job posting, which is one of the multiple job postings, to the recruitment slots for the second job posting, which is one of the multiple job postings.

The invention provides a recruitment method and device. The method comprises the steps of collecting video stream information and audio stream information of candidates of a to-be-recruitment post in an interview process and a structured text generated based on the audio stream information; based on the video stream information, the audio stream information and the structured text, determining a comprehensive emotion vector of the candidate; determining post skill vectors of the candidates based on the structured text; determining an emotion matching degree based on the post emotion demand vector of the to-be-recruited post and the comprehensive emotion vector; determining a skill matching degree based on the post skill demand vector and the post skill vector of the to-be-recruited post; and according to the emotion matching degree and the skill matching degree, determining the matching degree between the candidate and the to-be-recruited post. Through emotion and skill two-dimensional comprehensive evaluation, the intelligent level of the recruitment method is greatly improved, the recruitment decision is more scientific and accurate, and the quality and efficiency of enterprise talent selection are effectively improved.

The invention provides a decentralized anonymous recruitment method, an anonymous recruitment system and a storage medium, the method is applied to an intelligent contract of the anonymous recruitment system, the anonymous recruitment system further comprises a job hunting client and a recruitment client, and the method comprises the following steps: obtaining a position intention issued by the recruitment client; obtaining an anonymous qualification certificate corresponding to the position intention issued by the job application client, and verifying the anonymous qualification certificate; if the anonymous qualification certificate passes the verification, generating an anonymous request corresponding to the anonymous qualification certificate, and sending the anonymous request to the recruitment client, so that the recruitment client generates a recruitment intention according to the anonymous request; after the recruitment intention is received, performing position matching based on the anonymous qualification certificate and the position intention; and if the position matching is successful, obtaining identity data of the job seeker based on an authorization strategy, and sending the identity data to the recruitment client. According to the method, the problem of leakage of personal information on the resumes can be solved, resume information counterfeiting is avoided, time consumption for resume calling is reduced, the matching efficiency of mass resumes is improved, and the control right of job seekers for personal sensitive information of the job seekers is ensured.

The present invention provides a cloud recruitment method, system, platform, medium, and device based on rational job search assistance. The method includes: preliminarily matching target job seekers with enterprises based on cloud recruitment and establishing a recruitment relationship between the job seekers and the enterprises; providing rational job search assistance to the target job seekers; and allowing the target job seekers to choose whether to cancel the established recruitment relationship with the enterprise during the process of receiving the rational job search assistance. The rational job search assistance at least includes: assisting the target job seekers in entering the enterprise's virtual workplace for work experience; and / or assisting the target job seekers in entering the enterprise's virtual cultural scene for a quick overview. This method comprehensively and effectively solves the problem of job seekers' lack of rational decision-making during the job search process, ensuring that job seekers can fully consider underlying factors such as actual work conditions and corporate culture when making decisions, avoiding ignoring these key factors and thus avoiding a series of negative impacts on both job seekers and enterprises.

The invention provides an AI intelligent team building recruitment method and system, and the method comprises the steps: inputting the inputted team information, enterprise information and historical recruitment position information into an analysis unit of a team building model based on pre-training convergence, and generating a team building frame and a demand position; according to the input personnel information, a corresponding required position is matched, and the position of the required position is an existing position; and corresponding recruitment information is generated according to the remaining demand positions, and recruitment positions are published. According to the AI intelligent team establishment recruitment method and system, efficient and accurate team establishment is realized, and recruitment information of corresponding positions is published.

The invention relates to a recruitment method and device, computer equipment, a computer readable storage medium and a computer program product. The method comprises the steps of displaying an initial recruitment plan matched with a recruitment demand in response to an input operation of the recruitment demand; generating a target recruitment plan based on a feedback operation on the initial recruitment plan; and sequentially executing the recruitment links in the target recruitment plan until the recruitment plan is completed, and generating a recruitment result corresponding to the recruitment demand. By adopting the method, the recruitment efficiency can be improved.

The invention provides a game recruitment method. The game recruitment method comprises the following steps: displaying at least one recruitment entrance control on a chat channel interface; in response to a selection operation on the recruitment entry control, displaying a recruitment setting interface of a corresponding type; in response to a confirmation operation of recruitment information in the recruitment setting interface, generating recruitment information containing recruitment content; and publishing the recruitment information in the chat channel interface. According to the method, the visual recruitment entrance and the clear recruitment information display are provided, so that the interactive experience of players is improved, the players can quickly understand the recruitment content and make responses, the social team forming mechanism of the game is enriched, and the richness of the game is improved. Meanwhile, through structured recruitment information display, the technical problems of unclear information transmission and low team forming efficiency in the field of computer games are effectively solved.

The invention relates to a recruitment platform automatic recruitment method and system based on information matching, and belongs to the technical field of intelligent recruitment and human resource automation. The method comprises the following steps: obtaining recruitment page data information, and identifying a structural skeleton and a text abstract of the recruitment page data information through a document semantic hierarchy identification analysis method to obtain candidate structured recruitment elements; constructing a post portrait model according to the candidate structured recruitment elements, performing semantic alignment on the interaction element table and post portrait information one by one, and outputting post feature vectors; based on the post feature vectors, establishing an interview dialogue analysis framework, and performing alignment matching on the post portraits and the candidate portraits to generate a user portrait-post matching plan; and executing the user portrait-post matching plan, constructing a closed-loop matching optimization mechanism, and updating the candidate structured recruitment elements in real time.

The invention discloses a DRL and trust-based worker recruitment method under privacy protection, and aims to solve the problem of collaborative optimization of location privacy security, recruitment cost and data quality in a sparse mobile crowd sensing system. According to the method, worker and task position information is encrypted through a random matrix perturbation technology, and spatial matching and regional trust evaluation under privacy protection are realized by using characteristics of a lower triangular matrix trace; further constructing a key task selection model driven by deep reinforcement learning, modeling region selection as a Markov decision process, and inferring accuracy, trust coverage and recruitment cost through a near-end strategy optimization algorithm in combination with optimization data; meanwhile, a staged dynamic recruitment strategy is implemented, high-credibility workers are preferentially selected to guarantee task quality, and workers with unknown credibility are synchronously introduced to explore potential high-credibility workers. On the whole, a safe, efficient and low-cost solution is provided for worker recruitment and data acquisition in the sparse mobile crowd sensing system.