智能职业指导系统

Areej Kamal, Batul Naushad, Hadia Rafiq, S. Tahzeeb
{"title":"智能职业指导系统","authors":"Areej Kamal, Batul Naushad, Hadia Rafiq, S. Tahzeeb","doi":"10.1109/ICCIS54243.2021.9676408","DOIUrl":null,"url":null,"abstract":"We have developed a career guidance system that helps those students who are about to begin their higher education. Most of the time, students are not aware of what career path to follow or which academic major is in accordance with their interests. The system analyzes students' skills, abilities, and interests and recommends the five fields which are most suitable for them. This project helps students identify a specific domain that fits their skills and interests. Smart Career Guidance System is a web-based application built on the Django framework. We have deployed various Machine Learning techniques and algorithms to mimic a one-on-one meeting with an experienced career counselor. The data was collected in the form of a questionnaire that was based on Holland Occupational Themes and the Theory of Multiple Intelligences. A total of 392 graduates completed this online survey. SMOTE oversampling is used to evaluate the machine learning classifiers since the data is highly imbalanced. We tested XGBoost and Random Forest classifiers for recommending the best-suited career options which furnish AUC-ROC performance scores of 0.9952 and 0.9963 respectively. A fine-tuned version of the Random Forest Classifier has successfully attained an AUC-ROC performance score of 0.9976 which indicates the minimal false-positive rate. Ms. Areej Kamal, Ms. Hadia Rafiq and Ms. Batul Naushad have collaboratively conducted all activities of the project including data collection and cleaning, literature review, testing of ML models and development of the final solution. Mr. Shahab Tahzeeb directed and supervised all phases of the project with his immense knowledge and expertise.","PeriodicalId":165673,"journal":{"name":"2021 4th International Conference on Computing & Information Sciences (ICCIS)","volume":"6 9 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Smart Career Guidance System\",\"authors\":\"Areej Kamal, Batul Naushad, Hadia Rafiq, S. Tahzeeb\",\"doi\":\"10.1109/ICCIS54243.2021.9676408\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We have developed a career guidance system that helps those students who are about to begin their higher education. Most of the time, students are not aware of what career path to follow or which academic major is in accordance with their interests. The system analyzes students' skills, abilities, and interests and recommends the five fields which are most suitable for them. This project helps students identify a specific domain that fits their skills and interests. Smart Career Guidance System is a web-based application built on the Django framework. We have deployed various Machine Learning techniques and algorithms to mimic a one-on-one meeting with an experienced career counselor. The data was collected in the form of a questionnaire that was based on Holland Occupational Themes and the Theory of Multiple Intelligences. A total of 392 graduates completed this online survey. SMOTE oversampling is used to evaluate the machine learning classifiers since the data is highly imbalanced. We tested XGBoost and Random Forest classifiers for recommending the best-suited career options which furnish AUC-ROC performance scores of 0.9952 and 0.9963 respectively. A fine-tuned version of the Random Forest Classifier has successfully attained an AUC-ROC performance score of 0.9976 which indicates the minimal false-positive rate. Ms. Areej Kamal, Ms. Hadia Rafiq and Ms. Batul Naushad have collaboratively conducted all activities of the project including data collection and cleaning, literature review, testing of ML models and development of the final solution. Mr. Shahab Tahzeeb directed and supervised all phases of the project with his immense knowledge and expertise.\",\"PeriodicalId\":165673,\"journal\":{\"name\":\"2021 4th International Conference on Computing & Information Sciences (ICCIS)\",\"volume\":\"6 9 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-11-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 4th International Conference on Computing & Information Sciences (ICCIS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCIS54243.2021.9676408\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 4th International Conference on Computing & Information Sciences (ICCIS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCIS54243.2021.9676408","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2

摘要

我们开发了一个职业指导系统,帮助那些即将开始接受高等教育的学生。大多数时候,学生不知道应该走什么样的职业道路,也不知道哪个专业符合他们的兴趣。该系统分析学生的技能、能力和兴趣,并推荐最适合他们的五个领域。这个项目帮助学生确定适合他们技能和兴趣的特定领域。Smart Career Guidance System是一个基于Django框架的基于web的应用程序。我们已经部署了各种机器学习技术和算法来模拟与经验丰富的职业顾问的一对一会面。数据以问卷的形式收集,以荷兰职业主题和多元智能理论为基础。共有392名毕业生完成了这项在线调查。SMOTE过采样用于评估机器学习分类器,因为数据高度不平衡。我们测试了XGBoost和Random Forest分类器推荐最适合的职业选择,它们分别提供AUC-ROC性能得分为0.9952和0.9963。随机森林分类器的微调版本已经成功地获得了0.9976的AUC-ROC性能分数,这表明最小的假阳性率。Areej Kamal女士、Hadia Rafiq女士和Batul Naushad女士合作开展了项目的所有活动,包括数据收集和清理、文献综述、机器学习模型测试和最终解决方案的开发。Shahab Tahzeeb先生以其渊博的知识和专业知识指导和监督项目的所有阶段。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Smart Career Guidance System
We have developed a career guidance system that helps those students who are about to begin their higher education. Most of the time, students are not aware of what career path to follow or which academic major is in accordance with their interests. The system analyzes students' skills, abilities, and interests and recommends the five fields which are most suitable for them. This project helps students identify a specific domain that fits their skills and interests. Smart Career Guidance System is a web-based application built on the Django framework. We have deployed various Machine Learning techniques and algorithms to mimic a one-on-one meeting with an experienced career counselor. The data was collected in the form of a questionnaire that was based on Holland Occupational Themes and the Theory of Multiple Intelligences. A total of 392 graduates completed this online survey. SMOTE oversampling is used to evaluate the machine learning classifiers since the data is highly imbalanced. We tested XGBoost and Random Forest classifiers for recommending the best-suited career options which furnish AUC-ROC performance scores of 0.9952 and 0.9963 respectively. A fine-tuned version of the Random Forest Classifier has successfully attained an AUC-ROC performance score of 0.9976 which indicates the minimal false-positive rate. Ms. Areej Kamal, Ms. Hadia Rafiq and Ms. Batul Naushad have collaboratively conducted all activities of the project including data collection and cleaning, literature review, testing of ML models and development of the final solution. Mr. Shahab Tahzeeb directed and supervised all phases of the project with his immense knowledge and expertise.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信