候选人简历自动分割的NLP方法

M. Tikhonova, Anastasia Gavrishchuk
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引用次数: 3

摘要

只要能简化候选人的筛选过程,简历的分割和自动提取问题就变得越来越重要。本文提出了一种自动CV分割与解析的新方法。所描述的算法是基于自然语言处理和机器学习方法。拟议的程序允许从pdf或docx格式的简历中提取与候选人的工作经验和教育相关的信息。特别是,将简历分成3块(基本信息、教育背景和工作经历)。
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NLP methods for automatic candidate’s CV segmentation
The problem of CV (or resume) segmentation and automatic extraction becomes increasingly relevant nowadays as long as it could simplify candidate selection process. The paper proposes a new method of automatic CV segmentation and parsing. The described algorithm is based on Natural Language Processing and Machine Learning methods. The proposed procedure allows to extract information related to the candidates’ work experience and education from their CVs which come in pdf or docx format. In particular, CV segmentation into 3 blocks (Basic Information, Education and Work Experience) is performed.
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