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 proceedingConference Article in proceedingAcademicpeer-review


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 languageEnglish
Title of host publication2017 21st International Conference on Control Systems and Computer Science (CSCS)
EditorsIoan Dumitrache, Adina Magda Florea , Florin Pop, Alexandru Dumitrașcu
Place of PublicationBucharest
Number of pages7
Publication statusPublished - 7 Jul 2017
Externally publishedYes
Event21st Int. Conf. on Control Systems and Computer Science (CSCS21) - Bucharest, Romania
Duration: 29 May 201731 May 2017


Conference21st Int. Conf. on Control Systems and Computer Science (CSCS21)
Abbreviated titleCSCS21
Internet address


  • CV analysis
  • text cohesion
  • semantic relatedness
  • textual complexity
  • natural language processing


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