Potential Candidate Selection Using Information Extraction and Skyline Queries

  • Farzana YasminEmail author
  • Mohammad Imtiaz Nur
  • Mohammad Shamsul Arefin
Conference paper
Part of the Lecture Notes on Data Engineering and Communications Technologies book series (LNDECT, volume 49)


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 are 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, filter the candidates according to predefined rules and return the list of dominant candidates using skyline filtering.


Information extraction Natural language processing Machine learning Skyline query Candidate selection 



Informed consent was obtained from all individual participants included in the study.


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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Farzana Yasmin
    • 1
    Email author
  • Mohammad Imtiaz Nur
    • 1
  • Mohammad Shamsul Arefin
    • 1
  1. 1.Computer Science and EngineeringChittagong University of Engineering & TechnologyChattogramBangladesh

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