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

Dessi D.;Meloni A.;Reforgiato Recupero D.
2023-01-01

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.
2023
Inglese
Proceedings of the ACM Symposium on Applied Computing
9781450395175
Association for Computing Machinery
936
938
3
38th Annual ACM Symposium on Applied Computing, SAC 2023
Esperti anonimi
2023
est
scientifica
e-recruitment
natural language processing
recommendation
transformers
4 Contributo in Atti di Convegno (Proceeding)::4.1 Contributo in Atti di convegno
Alonso, R.; Dessi, D.; Meloni, A.; Reforgiato Recupero, D.
273
4
4.1 Contributo in Atti di convegno
none
info:eu-repo/semantics/conferencePaper
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