Hybrid Job and Resume Matcher

Nimet Tülümen, Gökhan Akgün, Ali Nohutçu, Günnur Sevgi Aktoros Genç, S. Genç
{"title":"Hybrid Job and Resume Matcher","authors":"Nimet Tülümen, Gökhan Akgün, Ali Nohutçu, Günnur Sevgi Aktoros Genç, S. Genç","doi":"10.1109/UBMK52708.2021.9558932","DOIUrl":null,"url":null,"abstract":"Information extraction from text data has always been a tricky and difficult task. This work follows a previous work regarding a designed system that matches job ads with resumes, then assigns them a scoring point. In this system, there are two main parts: information extraction and scoring. For the information extraction part, rule-based methods are efficient when the format of the resumes and job ads are known. In this paper, powerful and efficient methods for information extraction from the mixed resume format and job ads using machine learning and deep learning methods are proposed.","PeriodicalId":106516,"journal":{"name":"2021 6th International Conference on Computer Science and Engineering (UBMK)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2021-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 6th International Conference on Computer Science and Engineering (UBMK)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/UBMK52708.2021.9558932","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

Information extraction from text data has always been a tricky and difficult task. This work follows a previous work regarding a designed system that matches job ads with resumes, then assigns them a scoring point. In this system, there are two main parts: information extraction and scoring. For the information extraction part, rule-based methods are efficient when the format of the resumes and job ads are known. In this paper, powerful and efficient methods for information extraction from the mixed resume format and job ads using machine learning and deep learning methods are proposed.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
混合工作和简历匹配器
从文本数据中提取信息一直是一项棘手而困难的任务。这项工作遵循了之前的一项工作,该工作设计了一个系统,将招聘广告与简历相匹配,然后为它们分配一个计分点。在这个系统中,主要有两个部分:信息提取和评分。对于信息提取部分,当简历和招聘广告的格式已知时,基于规则的方法是有效的。本文提出了一种利用机器学习和深度学习方法从混合简历格式和招聘广告中提取信息的强大而高效的方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Emotion Analysis from Facial Expressions Using Convolutional Neural Networks Early Stage Fault Prediction via Inter-Project Rule Transfer Semantic Similarity Comparison of Word Representation Methods in the Field of Health Small Object Detection and Tracking from Aerial Imagery Anomaly Detection with Deep Long Short Term Memory Networks
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1