Lokesh. S, Mano Balaje. S, Prathish. E, B. Bharathi
{"title":"使用机器学习方法的简历筛选和推荐系统","authors":"Lokesh. S, Mano Balaje. S, Prathish. E, B. Bharathi","doi":"10.5121/cseij.2022.12101","DOIUrl":null,"url":null,"abstract":"Candidates apply in large numbers for jobs on web portals by uploading their resumes, due to the rapid growth of online-based recruitment systems. On the other hand, the resume has its formatting style, data blocks, and segments, as well as a variety of data formatting options such as text alignment, color, font type, and font size, making it an excellent example of unstructured data. As a result, filtering applicants for the appropriate position in an organization becomes a difficult task for recruiters. We can use Natural Language Processing (NLP) techniques to extract the relevant information from the resume to save time and effort. Also, a Machine Learning (ML) model is trained to check whether a candidate’s skills, experiences, and other aspects are suitable for that particular role. In addition to that, our system will also recommend the other available job roles based on the candidate’s skillset.","PeriodicalId":361871,"journal":{"name":"Computer Science & Engineering: An International Journal","volume":"137 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Resume Screening and Recommendation System using Machine Learning Approaches\",\"authors\":\"Lokesh. S, Mano Balaje. S, Prathish. E, B. Bharathi\",\"doi\":\"10.5121/cseij.2022.12101\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Candidates apply in large numbers for jobs on web portals by uploading their resumes, due to the rapid growth of online-based recruitment systems. On the other hand, the resume has its formatting style, data blocks, and segments, as well as a variety of data formatting options such as text alignment, color, font type, and font size, making it an excellent example of unstructured data. As a result, filtering applicants for the appropriate position in an organization becomes a difficult task for recruiters. We can use Natural Language Processing (NLP) techniques to extract the relevant information from the resume to save time and effort. Also, a Machine Learning (ML) model is trained to check whether a candidate’s skills, experiences, and other aspects are suitable for that particular role. In addition to that, our system will also recommend the other available job roles based on the candidate’s skillset.\",\"PeriodicalId\":361871,\"journal\":{\"name\":\"Computer Science & Engineering: An International Journal\",\"volume\":\"137 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-02-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Computer Science & Engineering: An International Journal\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.5121/cseij.2022.12101\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computer Science & Engineering: An International Journal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5121/cseij.2022.12101","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Resume Screening and Recommendation System using Machine Learning Approaches
Candidates apply in large numbers for jobs on web portals by uploading their resumes, due to the rapid growth of online-based recruitment systems. On the other hand, the resume has its formatting style, data blocks, and segments, as well as a variety of data formatting options such as text alignment, color, font type, and font size, making it an excellent example of unstructured data. As a result, filtering applicants for the appropriate position in an organization becomes a difficult task for recruiters. We can use Natural Language Processing (NLP) techniques to extract the relevant information from the resume to save time and effort. Also, a Machine Learning (ML) model is trained to check whether a candidate’s skills, experiences, and other aspects are suitable for that particular role. In addition to that, our system will also recommend the other available job roles based on the candidate’s skillset.