Resume assessment method and apparatus

Abstract

The invention discloses a resume assessment method. The method includes: obtaining a plurality of first resumes corresponding to a plurality of first feedback data comprising first feedback motion items, wherein the first feedback motion items express that the first resumes are associated with first feedback motions; constructing characteristic vectors of the plurality of first resumes as positivesamples, training an assessment model, and learning mapping relations between the characteristic vectors and the first feedback motion items; and calculating an assessment score of a to-be-assessed resume with regard to the first feedback motion item according to the mapping relation based on the characteristic vector of the to-be-assessed resume through the assessment model. The invention also discloses a resume assessment apparatus. According to the assessment scheme of the method and the apparatus, the relatively accurate assessment score can be given to the to-be-assessed resume by employing resume feedback data, and powerful technical assistance is provided for resume screeners.

Description

technical field [0001] The invention relates to the Internet field, 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 comprehensive recruitment websites (such as 51Job, Zhaopin.com) and Internet industry vertical recruitment websites (such as Lagou, Boss Zhipin) cover most of the middle and high-end job seekers. Under the circumstance 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 their competitiveness in the industry. [0003] At present, some mature technologies in this area mainly include: [0004] 1. Automatic analysis and information extraction of resume texts, using natural language understanding technology to extract key inform...

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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