Online self-service interview method based on natural language understanding

Abstract

The invention discloses an online self-service interview method based on natural language understanding, and the method comprises the steps: setting interview questions, question answers and questionweights, and generating an interview question bank; collecting resume information, wherein the resume information comprises a resume photo; based on the resume information, setting an evaluation rule,carrying out resume evaluation to obtain a resume evaluation result, and screening out a resume qualifier according to the resume evaluation result; enabling the resume qualifier to continue to participate in the network video interview, outputting questions and starting questioning, storing answer content of the interviewee in a system, carrying out semantic matching on the answer content and the question answers, and based on the semantic matching, obtaining related questions in the interview question bank and starting the next questioning; and based on the semantic matching, obtaining theanswer accuracy of the interviewee, and making interview evaluation.

Description

Technical field[0001]The embodiments of the present invention relate to the field of computer technology, and in particular to an online self-service interview method based on natural language understanding.Background technique[0002]With the rapid development of computer technology, various industries have set off a wave of application of computer technology to promote the development of the industry.[0003]In recent years, the number of employees has increased greatly. For large enterprises, talents play a vital role in the development of enterprises. During the peak period of corporate recruitment, a large number of resumes are often received. At present, the general process for most companies to recruit talents is to manually select resumes, and correspondingly to those who have passed the screening, organize human resources for preliminary interviews, and further select personnel based on the evaluation after the preliminary interviews to enter the next interview.[0004]During the...

AI Technical Summary

Problems solved by technology

[0004] During the initial interview, a lot of manpower and time resources will be consumed, the questions asked by the interviewer are not consistent, and there is no unified evaluation standard

In addition, it will be difficult for interviewers and a large number of applicants to determine the time point for intensive interviews

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