A resume evaluation method and device

Abstract

The invention discloses a resume evaluation method, comprising: acquiring a plurality of first resumes corresponding to a plurality of first feedback data including first feedback action items and first screener information, wherein the first feedback action items represent the first A resume is associated with the first feedback action; feature vectors are constructed for a plurality of first resumes as a plurality of positive samples to train an evaluation model to learn the mapping relationship between the feature vectors and the first feedback action items; The evaluation score of the resume to be evaluated with respect to the first feedback action item is calculated from the feature vector of the evaluation resume according to the mapping relationship. The invention also discloses a resume evaluation device. Through the evaluation scheme of the embodiment of the present invention, a personalized recommendation reference can be provided for a resume screener.

Description

technical field [0001] The present invention relates to the field of Internet, in particular to a resume evaluation method and device. Background technique [0002] In recent years, with the development of Internet technology, the Internetization of the talent recruitment market has already become the mainstream. Large-scale comprehensive recruitment websites (such as 51Job, Zhaopin) and vertical recruitment websites in the Internet industry (such as Lagou, Boss Zhipin) cover most of the mid-to-high-end job seekers. In the case that the resumes of job seekers are generally digitized, how to use technology to help companies improve the efficiency of talent recruitment is an important issue for recruitment websites to enhance the competitiveness of the industry. [0003] At present, some mature technologies in this area mainly include: [0004] 1. Automatic analysis of resume text and information extraction, using natural language understanding technology to extract key info...

AI Technical Summary

Problems solved by technology

[0007] Although the above three types of technologies are all helpful to improve the efficiency of enterprise talent recruitment, these technologies focus on using natural language processing technology to match the information in each resume according to the needs of enterprise employment, and only play the role of primary selection. The immobilization of the conditions will lead to the missing of some suitable candidates. In many cases, the resume screeners still need to check the resumes one by one, so the help for the resume screeners is limited.

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