A Resume Screening Method for Campus Recruitment

Abstract

The invention provides a resume screening method for campus recruitment. The specific method includes: formulating a resume template for campus recruitment, establishing component modules and indicators; importing resume data and evaluation data; calculating scores in the module, and segmenting the objective ability of candidates Evaluation or linear evaluation, using the TF‑IDF method to calculate the text matching degree of the candidates’ subjective description texts, including project job descriptions and internship job descriptions; using Analytic Hierarchy Process (AHP) to set scale values ​​between indicators, and calculate The weights of each module and indicator; use the TOPSIS method to calculate the distance between the candidate's score and the ideal solution, and rank the candidate's matching degree accordingly.

Description

technical field [0001] The invention relates to the field of information technology, in particular to a resume screening method for campus recruitment. Background technique [0002] In the traditional recruitment process, a large number of recruiters are required to be manually responsible for multiple interviews and screening processes, which consumes a lot of manpower and time. [0003] In order to make the resume screening process more intelligent, some scholars have adopted different screening models for information extraction and score calculation of resumes, but they all have certain deficiencies: some models do not specify the calculation methods of all indicators in the resume, so they cannot be calculated. The final matching result; some models only score long text descriptions in the resume, or only score objective indicators, and the content of the consideration is not comprehensive; some models use the method of directly setting weights, which lacks objective sci...

AI Technical Summary

Problems solved by technology

[0002] In the traditional recruitment process, a large number of recruiters are manually responsible for multiple interviews and screening processes, which will consume a lot of manpower and time

[0003] In order to make the resume screening process more intelligent, some scholars have adopted different screening models for resume information extraction and score calculation, but there are certain shortcomings: some models do not specify the calculation methods of all indicators in the resume, so they cannot be calculated The final matching result; some models only score long text descriptions in resumes, or only score objective indicators, and the content of consideration is not comprehensive enough; some models use the method of directly setting weights, which lacks objective scientificity; some models The screening model is only established for a specific position, which lacks universal applicability; the index establishment of most models is not suitable for the recruitment needs of school recruitment

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