How Adequate is your CV? Analyzing French CVs with ReaderBench

Gabriel Gutu; Mihai Dascalu; Stefan Trausan-Matu; Olivier Lepoivre

doi:10.1109/CSCS.2017.85

How Adequate is your CV? Analyzing French CVs with ReaderBench

Gabriel Gutu, Mihai Dascalu, Stefan Trausan-Matu, Olivier Lepoivre

Research output: Chapter in Book/Report/Conference proceeding › Conference Article in proceeding › Academic › peer-review

Abstract

This study is aimed at presenting a new ReaderBench-based tool built to support candidates in increasing the quality of their CV for a job opening. Both the visual quality and the textual content are considered while also providing an overview and corresponding feedback for the entire CV. The presented CV analysis tool uses advanced Natural Language Processing techniques to interpret and understand the content from written texts, while also considering their visual traits. The study was performed on a collection of more than 50 CVs that were manually annotated as positive or negative in terms of their visual and content-oriented aspects. A statistical analysis based on more than 400 textual indices was performed on the training corpora in order to extract the traits that define a good commercial CV. The results enabled us to build an online tool accessible on our website that provides recommendations for CVs written in French language.

Original language	English
Title of host publication	2017 21st International Conference on Control Systems and Computer Science (CSCS)
Editors	Ioan Dumitrache, Adina Magda Florea , Florin Pop, Alexandru Dumitrașcu
Place of Publication	Bucharest
Publisher	IEEE
Pages	559-565
Number of pages	7
DOIs	https://doi.org/10.1109/CSCS.2017.85
Publication status	Published - 7 Jul 2017
Externally published	Yes
Event	21st Int. Conf. on Control Systems and Computer Science (CSCS21) - Bucharest, Romania Duration: 29 May 2017 → 31 May 2017 https://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=7963998 https://cscs21.hpc.pub.ro/

Conference

Conference	21st Int. Conf. on Control Systems and Computer Science (CSCS21)
Abbreviated title	CSCS21
Country/Territory	Romania
City	Bucharest
Period	29/05/17 → 31/05/17
Internet address	https://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=7963998 https://cscs21.hpc.pub.ro/

Keywords

CV analysis
text cohesion
semantic relatedness
textual complexity
natural language processing

Access to Document

10.1109/CSCS.2017.85Licence: CC BY-NC-SA

https://www.researchgate.net/publication/318295779_How_Adequate_Is_Your_CV_Analyzing_French_CVs_with_ReaderBenchLicence: CC BY-NC-SA

Rage: Realising an Applied Gaming Eco-system
Westera, W. (PI), Georgiadis, K. (CoI), Saveski, G. (CoI), van Lankveld, G. (CoI), Bahreini, K. (CoI), van der Vegt, W. (CoI), Berkhout, J. (CoI), Nyamsuren, E. (CoI), Kluijfhout, E. (CoI) & Nadolski, R. (CoI)
European Union
1/02/15 → 31/07/19
Project: Research

Cite this

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title = "How Adequate is your CV? Analyzing French CVs with ReaderBench",

abstract = "This study is aimed at presenting a new ReaderBench-based tool built to support candidates in increasing the quality of their CV for a job opening. Both the visual quality and the textual content are considered while also providing an overview and corresponding feedback for the entire CV. The presented CV analysis tool uses advanced Natural Language Processing techniques to interpret and understand the content from written texts, while also considering their visual traits. The study was performed on a collection of more than 50 CVs that were manually annotated as positive or negative in terms of their visual and content-oriented aspects. A statistical analysis based on more than 400 textual indices was performed on the training corpora in order to extract the traits that define a good commercial CV. The results enabled us to build an online tool accessible on our website that provides recommendations for CVs written in French language.",

keywords = "CV analysis, text cohesion, semantic relatedness, textual complexity, natural language processing",

author = "Gabriel Gutu and Mihai Dascalu and Stefan Trausan-Matu and Olivier Lepoivre",

year = "2017",

month = jul,

day = "7",

doi = "10.1109/CSCS.2017.85",

language = "English",

pages = "559--565",

editor = "Ioan Dumitrache and {Florea }, {Adina Magda} and Florin Pop and Alexandru Dumitrașcu",

booktitle = "2017 21st International Conference on Control Systems and Computer Science (CSCS)",

publisher = "IEEE",

address = "United States",

note = "21st Int. Conf. on Control Systems and Computer Science (CSCS21), CSCS21 ; Conference date: 29-05-2017 Through 31-05-2017",

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Gutu, G, Dascalu, M, Trausan-Matu, S & Lepoivre, O 2017, How Adequate is your CV? Analyzing French CVs with ReaderBench. in I Dumitrache, AM Florea , F Pop & A Dumitrașcu (eds), 2017 21st International Conference on Control Systems and Computer Science (CSCS). IEEE, Bucharest, pp. 559-565, 21st Int. Conf. on Control Systems and Computer Science (CSCS21), Bucharest, Romania, 29/05/17. https://doi.org/10.1109/CSCS.2017.85

How Adequate is your CV? Analyzing French CVs with ReaderBench. / Gutu, Gabriel; Dascalu, Mihai; Trausan-Matu, Stefan et al.
2017 21st International Conference on Control Systems and Computer Science (CSCS). ed. / Ioan Dumitrache; Adina Magda Florea ; Florin Pop; Alexandru Dumitrașcu. Bucharest: IEEE, 2017. p. 559-565.

Research output: Chapter in Book/Report/Conference proceeding › Conference Article in proceeding › Academic › peer-review

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T1 - How Adequate is your CV? Analyzing French CVs with ReaderBench

AU - Gutu, Gabriel

AU - Dascalu, Mihai

AU - Trausan-Matu, Stefan

AU - Lepoivre, Olivier

PY - 2017/7/7

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N2 - This study is aimed at presenting a new ReaderBench-based tool built to support candidates in increasing the quality of their CV for a job opening. Both the visual quality and the textual content are considered while also providing an overview and corresponding feedback for the entire CV. The presented CV analysis tool uses advanced Natural Language Processing techniques to interpret and understand the content from written texts, while also considering their visual traits. The study was performed on a collection of more than 50 CVs that were manually annotated as positive or negative in terms of their visual and content-oriented aspects. A statistical analysis based on more than 400 textual indices was performed on the training corpora in order to extract the traits that define a good commercial CV. The results enabled us to build an online tool accessible on our website that provides recommendations for CVs written in French language.

AB - This study is aimed at presenting a new ReaderBench-based tool built to support candidates in increasing the quality of their CV for a job opening. Both the visual quality and the textual content are considered while also providing an overview and corresponding feedback for the entire CV. The presented CV analysis tool uses advanced Natural Language Processing techniques to interpret and understand the content from written texts, while also considering their visual traits. The study was performed on a collection of more than 50 CVs that were manually annotated as positive or negative in terms of their visual and content-oriented aspects. A statistical analysis based on more than 400 textual indices was performed on the training corpora in order to extract the traits that define a good commercial CV. The results enabled us to build an online tool accessible on our website that provides recommendations for CVs written in French language.

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KW - semantic relatedness

KW - textual complexity

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A2 - Florea , Adina Magda

A2 - Pop, Florin

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ER -

How Adequate is your CV? Analyzing French CVs with ReaderBench

Abstract

Conference

Keywords

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Rage: Realising an Applied Gaming Eco-system

Cite this