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

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
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引用次数: 0

摘要

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。
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A General and NLP-based Architecture to perform Recommendation: A Use Case for Online Job Search and Skills Acquisition
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.
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来源期刊
Applied Computing Review
Applied Computing Review COMPUTER SCIENCE, INFORMATION SYSTEMS-
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40.00%
发文量
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