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Potential Candidate selection using Information Extraction and Skyline Queries

EasyChair Preprint no. 1677

20 pagesDate: October 16, 2019


Information extraction is a mechanism for devising an automatic method for text management. In the case of candidate recruitment, nowadays different companies ask the applicants to submit their applications or resumes in the form of electronic documents. In general, there are huge numbers of resumes dropped and therefore the volume of the documents increases. Extracting information and choosing the best candidates from all these documents manually is very difficult and time-consuming. In order to make the recruitment process easier for the companies, we have developed a framework that takes the resumes of candidates as well as the priorities of the employer as input, extract information of the candidates using Natural Language Processing (NLP) from the resumes, rank the candidates according to predefined rules and return the list of dominant candidates using skyline filtering.

Keyphrases: Candidate Selection, Information Extraction, Natural Language Processing, Skyline query

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
  author = {Farzana Yasmin and Mohammad Imtiaz Nur and Mohammad Shamsul Arefin},
  title = {Potential Candidate selection using Information Extraction and Skyline Queries},
  howpublished = {EasyChair Preprint no. 1677},

  year = {EasyChair, 2019}}
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