Recommendation System: A New Approach to Recommend Potential Profile Using AHP Method

Safia Baali
{"title":"Recommendation System: A New Approach to Recommend Potential Profile Using AHP Method","authors":"Safia Baali","doi":"10.4018/ijaiml.20210701.oa11","DOIUrl":null,"url":null,"abstract":"The most challenging problem in human resources specially in the IT digital services company, is to assign the best collaborator’s in the adequate project , then ensure the delivery’s performance.in this paper we aim to develop à recommandation System using based-content and collaborative filtering in order to recommend potential profiles for a new job offer. The Principal parts of this recommandation is the matching between job offer of new project and collaborators profiles and the scoring using AHP method. In the first step we propose a model of criteria to measure collective skills , we validate by a survey realized in the IT service company , we analyze the data collected using PCA method (Principal Component Analysis).the results indicate six factors to measure collective skills of each collaborator (Technical skill, Proactivity ,Integrity, Cooperation, Communication and Benevolence/Interpersonal Relationship), these factors are used in AHP function to give score for each collaborator then allow the recommendation for the adequate project.","PeriodicalId":217541,"journal":{"name":"Int. J. Artif. Intell. Mach. Learn.","volume":"33 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Int. J. Artif. Intell. Mach. Learn.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4018/ijaiml.20210701.oa11","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

The most challenging problem in human resources specially in the IT digital services company, is to assign the best collaborator’s in the adequate project , then ensure the delivery’s performance.in this paper we aim to develop à recommandation System using based-content and collaborative filtering in order to recommend potential profiles for a new job offer. The Principal parts of this recommandation is the matching between job offer of new project and collaborators profiles and the scoring using AHP method. In the first step we propose a model of criteria to measure collective skills , we validate by a survey realized in the IT service company , we analyze the data collected using PCA method (Principal Component Analysis).the results indicate six factors to measure collective skills of each collaborator (Technical skill, Proactivity ,Integrity, Cooperation, Communication and Benevolence/Interpersonal Relationship), these factors are used in AHP function to give score for each collaborator then allow the recommendation for the adequate project.
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
推荐系统:一种基于AHP方法的潜在剖面推荐新方法
人力资源中最具挑战性的问题,特别是在IT数字服务公司,是在适当的项目中分配最佳的合作者,然后确保交付的性能。在本文中,我们的目标是开发一个基于内容和协同过滤的推荐系统,以便为新的工作机会推荐潜在的个人资料。该建议的主要部分是新项目的工作机会与合作者的个人资料之间的匹配,并使用AHP方法进行评分。在第一步中,我们提出了一个衡量集体技能的标准模型,我们通过在IT服务公司中实现的调查来验证,我们使用主成分分析(PCA)方法分析收集的数据。结果表明,衡量每个合作者的集体技能的六个因素(技术技能,主动性,完整性,合作,沟通和仁慈/人际关系),这些因素在AHP函数中被用来给每个合作者打分,然后允许推荐合适的项目。
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
Analysis and Implications of Adopting AI and Machine Learning in Marketing, Servicing, and Communications Technology Survey of Recent Applications of Artificial Intelligence for Detection and Analysis of COVID-19 and Other Infectious Diseases Boosting Convolutional Neural Networks Using a Bidirectional Fast Gated Recurrent Unit for Text Categorization Using Open-Source Software for Business, Urban, and Other Applications of Deep Neural Networks, Machine Learning, and Data Analytics Tools Autonomous Navigation Using Deep Reinforcement Learning in ROS
×
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