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Occupational profiling driven by online job advertisements: Taking the data analysis and processing engineering technicians as an example

The occupational profiling system driven by the traditional survey method has some shortcomings such as lag in updating, time consumption and laborious revision. It is necessary to refine and improve the traditional occupational portrait system through dynamic occupational information. Under the cir...

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Detalles Bibliográficos
Autores principales: Cao, Lina, Zhang, Jian, Ge, Xinquan, Chen, Jindong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8219172/
https://www.ncbi.nlm.nih.gov/pubmed/34157028
http://dx.doi.org/10.1371/journal.pone.0253308
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author Cao, Lina
Zhang, Jian
Ge, Xinquan
Chen, Jindong
author_facet Cao, Lina
Zhang, Jian
Ge, Xinquan
Chen, Jindong
author_sort Cao, Lina
collection PubMed
description The occupational profiling system driven by the traditional survey method has some shortcomings such as lag in updating, time consumption and laborious revision. It is necessary to refine and improve the traditional occupational portrait system through dynamic occupational information. Under the circumstances of big data, this paper showed the feasibility of vocational portraits driven by job advertisements with data analysis and processing engineering technicians (DAPET) as an example. First, according to the description of occupation in the Chinese Occupation Classification Grand Dictionary, a text similarity algorithm was used to preliminarily choose recruitment data with high similarity. Second, Convolutional Neural Networks for Sentence Classification (TextCNN) was used to further classify the preliminary corpus to obtain a precise occupational dataset. Third, the specialty and skill were taken as named entities that were automatically extracted by the named entity recognition technology. Finally, putting the extracted entities into the occupational dataset, the occupation characteristics of multiple dimensions were depicted to form a profile of the vocation.
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spelling pubmed-82191722021-07-07 Occupational profiling driven by online job advertisements: Taking the data analysis and processing engineering technicians as an example Cao, Lina Zhang, Jian Ge, Xinquan Chen, Jindong PLoS One Research Article The occupational profiling system driven by the traditional survey method has some shortcomings such as lag in updating, time consumption and laborious revision. It is necessary to refine and improve the traditional occupational portrait system through dynamic occupational information. Under the circumstances of big data, this paper showed the feasibility of vocational portraits driven by job advertisements with data analysis and processing engineering technicians (DAPET) as an example. First, according to the description of occupation in the Chinese Occupation Classification Grand Dictionary, a text similarity algorithm was used to preliminarily choose recruitment data with high similarity. Second, Convolutional Neural Networks for Sentence Classification (TextCNN) was used to further classify the preliminary corpus to obtain a precise occupational dataset. Third, the specialty and skill were taken as named entities that were automatically extracted by the named entity recognition technology. Finally, putting the extracted entities into the occupational dataset, the occupation characteristics of multiple dimensions were depicted to form a profile of the vocation. Public Library of Science 2021-06-22 /pmc/articles/PMC8219172/ /pubmed/34157028 http://dx.doi.org/10.1371/journal.pone.0253308 Text en © 2021 Cao et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Cao, Lina
Zhang, Jian
Ge, Xinquan
Chen, Jindong
Occupational profiling driven by online job advertisements: Taking the data analysis and processing engineering technicians as an example
title Occupational profiling driven by online job advertisements: Taking the data analysis and processing engineering technicians as an example
title_full Occupational profiling driven by online job advertisements: Taking the data analysis and processing engineering technicians as an example
title_fullStr Occupational profiling driven by online job advertisements: Taking the data analysis and processing engineering technicians as an example
title_full_unstemmed Occupational profiling driven by online job advertisements: Taking the data analysis and processing engineering technicians as an example
title_short Occupational profiling driven by online job advertisements: Taking the data analysis and processing engineering technicians as an example
title_sort occupational profiling driven by online job advertisements: taking the data analysis and processing engineering technicians as an example
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8219172/
https://www.ncbi.nlm.nih.gov/pubmed/34157028
http://dx.doi.org/10.1371/journal.pone.0253308
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