A Format-sensitive BERT-based Approach to Resume Segmentation
In the early stages of a recruitment process, recruiters can spend a lot of time analyzing resumes (CVs) manually. This has led to the development of machine learning methods for the automated analysis of such documents, which currently besides text encompass rich formatting. Since rich formatting i...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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FRUCT
2023-05-01
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| Series: | Proceedings of the XXth Conference of Open Innovations Association FRUCT |
| Subjects: | |
| Online Access: | https://www.fruct.org/publications/volume-33/fruct33/files/Esp.pdf |
| _version_ | 1797807535357427712 |
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| author | Albeiro Espinal Yannis Haralambous Dominique Bedart John Puentes |
| author_facet | Albeiro Espinal Yannis Haralambous Dominique Bedart John Puentes |
| author_sort | Albeiro Espinal |
| collection | DOAJ |
| description | In the early stages of a recruitment process, recruiters can spend a lot of time analyzing resumes (CVs) manually. This has led to the development of machine learning methods for the automated analysis of such documents, which currently besides text encompass rich formatting. Since rich formatting is not considered in any of the automated analysis stages and its possible impact has not been studied, this article investigates how to extract, transform, and apply grapholinguistic content. To this end, we propose a format sensitive and BERT-based framework for the essential first step in CV analysis, i.e. segmentation, relating the automatic description of graphic and textual markers, transformed in linguistic variables by means of fuzzification, to identify dependencies and semantic relationships with the recruiters’ manual segmentation. Using a training dataset of 150 resumes, our approach achieved an F1-Score of 89% when segmenting 153 new samples. |
| first_indexed | 2024-03-13T06:24:01Z |
| format | Article |
| id | doaj.art-a71368b0c4bd4c5892918adacf192801 |
| institution | Directory Open Access Journal |
| issn | 2305-7254 2343-0737 |
| language | English |
| last_indexed | 2024-03-13T06:24:01Z |
| publishDate | 2023-05-01 |
| publisher | FRUCT |
| record_format | Article |
| series | Proceedings of the XXth Conference of Open Innovations Association FRUCT |
| spelling | doaj.art-a71368b0c4bd4c5892918adacf1928012023-06-09T11:41:51ZengFRUCTProceedings of the XXth Conference of Open Innovations Association FRUCT2305-72542343-07372023-05-01331303710.23919/FRUCT58615.2023.10143072A Format-sensitive BERT-based Approach to Resume SegmentationAlbeiro Espinal0Yannis Haralambous1Dominique Bedart2John Puentes3IMT Atlantique, Lab-STICC, CNRS UMR 6285.IMT AtlantiqueDSI Global ServicesIMT Atlantique, Lab-STICC, CNRS UMR 6285In the early stages of a recruitment process, recruiters can spend a lot of time analyzing resumes (CVs) manually. This has led to the development of machine learning methods for the automated analysis of such documents, which currently besides text encompass rich formatting. Since rich formatting is not considered in any of the automated analysis stages and its possible impact has not been studied, this article investigates how to extract, transform, and apply grapholinguistic content. To this end, we propose a format sensitive and BERT-based framework for the essential first step in CV analysis, i.e. segmentation, relating the automatic description of graphic and textual markers, transformed in linguistic variables by means of fuzzification, to identify dependencies and semantic relationships with the recruiters’ manual segmentation. Using a training dataset of 150 resumes, our approach achieved an F1-Score of 89% when segmenting 153 new samples.https://www.fruct.org/publications/volume-33/fruct33/files/Esp.pdfresume segmentation format-sensitive analysis of resumes resume ontology bert-based resume segmentation |
| spellingShingle | Albeiro Espinal Yannis Haralambous Dominique Bedart John Puentes A Format-sensitive BERT-based Approach to Resume Segmentation Proceedings of the XXth Conference of Open Innovations Association FRUCT resume segmentation format-sensitive analysis of resumes resume ontology bert-based resume segmentation |
| title | A Format-sensitive BERT-based Approach to Resume Segmentation |
| title_full | A Format-sensitive BERT-based Approach to Resume Segmentation |
| title_fullStr | A Format-sensitive BERT-based Approach to Resume Segmentation |
| title_full_unstemmed | A Format-sensitive BERT-based Approach to Resume Segmentation |
| title_short | A Format-sensitive BERT-based Approach to Resume Segmentation |
| title_sort | format sensitive bert based approach to resume segmentation |
| topic | resume segmentation format-sensitive analysis of resumes resume ontology bert-based resume segmentation |
| url | https://www.fruct.org/publications/volume-33/fruct33/files/Esp.pdf |
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