{"title":"Intelligent Recruitment System Using NLP","authors":"Anushka Sharma, Smiti Singhal, Dhara Ajudia","doi":"10.1109/aimv53313.2021.9670958","DOIUrl":null,"url":null,"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.","PeriodicalId":135318,"journal":{"name":"2021 International Conference on Artificial Intelligence and Machine Vision (AIMV)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 International Conference on Artificial Intelligence and Machine Vision (AIMV)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/aimv53313.2021.9670958","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
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.