License: Creative Commons Attribution 4.0 International license (CC BY 4.0)
When quoting this document, please refer to the following
DOI: 10.4230/OASIcs.LDK.2021.25
URN: urn:nbn:de:0030-drops-145612
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Urbano, Joana ; Couto, Miguel ; Rocha, Gil ; Lopes Cardoso, Henrique

Inconsistency Detection in Job Postings

OASIcs-LDK-2021-25.pdf (0.6 MB)


The use of AI in recruitment is growing and there is AI software that reads jobs' descriptions in order to select the best candidates for these jobs. However, it is not uncommon for these descriptions to contain inconsistencies such as contradictions and ambiguities, which confuses job candidates and fools the AI algorithm. In this paper, we present a model based on natural language processing (NLP), machine learning (ML), and rules to detect these inconsistencies in the description of language requirements and to alert the recruiter to them, before the job posting is published. We show that the use of an hybrid model based on ML techniques and a set of domain-specific rules to extract the language details from sentences achieves high performance in the detection of inconsistencies.

BibTeX - Entry

  author =	{Urbano, Joana and Couto, Miguel and Rocha, Gil and Lopes Cardoso, Henrique},
  title =	{{Inconsistency Detection in Job Postings}},
  booktitle =	{3rd Conference on Language, Data and Knowledge (LDK 2021)},
  pages =	{25:1--25:16},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-199-3},
  ISSN =	{2190-6807},
  year =	{2021},
  volume =	{93},
  editor =	{Gromann, Dagmar and S\'{e}rasset, Gilles and Declerck, Thierry and McCrae, John P. and Gracia, Jorge and Bosque-Gil, Julia and Bobillo, Fernando and Heinisch, Barbara},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{},
  URN =		{urn:nbn:de:0030-drops-145612},
  doi =		{10.4230/OASIcs.LDK.2021.25},
  annote =	{Keywords: NLP, Ambiguities, Contradictions, Recruitment software}

Keywords: NLP, Ambiguities, Contradictions, Recruitment software
Collection: 3rd Conference on Language, Data and Knowledge (LDK 2021)
Issue Date: 2021
Date of publication: 30.08.2021

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