10 results about "Recruitment methods" patented technology

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 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 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.