A General and NLP-based Architecture to perform Recommendation: A Use Case for Online Job Search and Skills Acquisition

IF 0.4 Q4 COMPUTER SCIENCE, INFORMATION SYSTEMS Applied Computing Review Pub Date : 2023-03-27 DOI:10.1145/3555776.3577844
Rubén Alonso, D. Dessí, Antonello Meloni, Diego Reforgiato Recupero
{"title":"A General and NLP-based Architecture to perform Recommendation: A Use Case for Online Job Search and Skills Acquisition","authors":"Rubén Alonso, D. Dessí, Antonello Meloni, Diego Reforgiato Recupero","doi":"10.1145/3555776.3577844","DOIUrl":null,"url":null,"abstract":"Natural Language Processing (NLP) is crucial to perform recommendations of items that can be only described by natural language. However, NLP usage within recommendation modules is difficult and usually requires a relevant initial effort, thus limiting its widespread adoption. To overcome this limitation, we introduce FORESEE, a novel architecture that can be instantiated with NLP and Machine Learning (ML) modules to perform recommendations of items that are described by natural language features. Furthermore, we describe an instantiation of such architecture to provide a service for the job market where applicants can verify whether their curriculum vitae (CV) is eligible for a given job position, can receive suggestions about which skills and abilities they should obtain, and finally, can obtain recommendations about online resources which might strengthen their CVs.","PeriodicalId":42971,"journal":{"name":"Applied Computing Review","volume":null,"pages":null},"PeriodicalIF":0.4000,"publicationDate":"2023-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Applied Computing Review","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3555776.3577844","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
引用次数: 0

Abstract

Natural Language Processing (NLP) is crucial to perform recommendations of items that can be only described by natural language. However, NLP usage within recommendation modules is difficult and usually requires a relevant initial effort, thus limiting its widespread adoption. To overcome this limitation, we introduce FORESEE, a novel architecture that can be instantiated with NLP and Machine Learning (ML) modules to perform recommendations of items that are described by natural language features. Furthermore, we describe an instantiation of such architecture to provide a service for the job market where applicants can verify whether their curriculum vitae (CV) is eligible for a given job position, can receive suggestions about which skills and abilities they should obtain, and finally, can obtain recommendations about online resources which might strengthen their CVs.
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
执行推荐的通用和基于nlp的架构:用于在线工作搜索和技能获取的用例
自然语言处理(NLP)对于执行只能用自然语言描述的项目的推荐至关重要。然而,在推荐模块中使用NLP是困难的,通常需要相关的初始努力,从而限制了它的广泛采用。为了克服这一限制,我们引入了FORESEE,这是一种新颖的架构,可以用NLP和机器学习(ML)模块实例化,以执行由自然语言特征描述的项目的推荐。此外,我们描述了这种架构的一个实例,为就业市场提供服务,申请人可以验证他们的简历(CV)是否符合给定的工作职位,可以收到关于他们应该获得哪些技能和能力的建议,最后可以获得有关在线资源的建议,这可能会加强他们的简历。
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
Applied Computing Review
Applied Computing Review COMPUTER SCIENCE, INFORMATION SYSTEMS-
自引率
40.00%
发文量
8
期刊最新文献
DIWS-LCR-Rot-hop++: A Domain-Independent Word Selector for Cross-Domain Aspect-Based Sentiment Classification Leveraging Semantic Technologies for Collaborative Inference of Threatening IoT Dependencies Relating Optimal Repairs in Ontology Engineering with Contraction Operations in Belief Change Block-RACS: Towards Reputation-Aware Client Selection and Monetization Mechanism for Federated Learning Elastic Data Binning: Time-Series Sketching for Time-Domain Astrophysics Analysis
×
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