Intelligent Recruitment System Using NLP

Anushka Sharma, Smiti Singhal, Dhara Ajudia
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引用次数: 1

Abstract

India has the highest population of youths and unemployment is still a major problem. Even though a lot of job opportunities are coming in Pharmaceutical, Business Management, Information Technology, Instructors, Billing Counter, Accounts, Textile Business, Food Industries, Tourism, and many more fields, the number of applications is significantly higher. Eligible candidates and suitable jobs are the prime requirements of a recruiter and a candidate respectively. As per census 2011, 19.1% of the Indian population was constituted of Youth which was expected to become around 34% of the total population by the year 2020. Every day, thousands to lakhs of applications are being received for jobs against few vacancies. Recruiters generally screen the resumes manually for the selection of candidates. Going through every candidate’s resume in detail to evaluate them based on the skills, experience, and abilities they possess would take a long time for the recruiter. So, in the practical world, they would only be able to read limited resumes which would lead to organizations losing out on the quality of selection. The paper focuses on extracting data from resumes and performing the required analysis on the data to convert it into useful information for the recruiters. Thus, the Resume Parser would help the recruiters to select the best relevant candidates in a minimal amount of time, consequently saving their time and effort.
基于NLP的智能招聘系统
印度拥有最多的青年人口,失业仍然是一个主要问题。尽管在制药、商业管理、信息技术、教师、记账、会计、纺织、食品工业、旅游等许多领域都有大量的工作机会,但申请数量明显更高。合格的候选人和合适的工作分别是招聘人员和候选人的首要要求。根据2011年的人口普查,19.1%的印度人口是青年,预计到2020年将占总人口的34%左右。每天都会收到成千上万的求职申请,而职位空缺却很少。招聘人员通常会手动筛选简历以选择候选人。仔细阅读每个求职者的简历,根据他们所拥有的技能、经验和能力对他们进行评估,这会花费招聘人员很长时间。因此,在现实世界中,他们只能阅读有限的简历,这将导致组织失去选择的质量。本文的重点是从简历中提取数据,并对数据进行必要的分析,将其转化为对招聘人员有用的信息。因此,简历解析器将帮助招聘人员在最短的时间内选择最合适的候选人,从而节省他们的时间和精力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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