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DOI: 10.14569/IJACSA.2019.0101245
PDF

Developing a Framework for Potential Candidate Selection

Author 1: Farzana Yasmin
Author 2: Mohammad Imtiaz Nur
Author 3: Mohammad Shamsul Arefin

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 10 Issue 12, 2019.

  • Abstract and Keywords
  • How to Cite this Article
  • {} BibTeX Source

Abstract: Recruitment is the process of hiring the right person for the right job. In the current competitive world, recruiting the right person from thousands of applicants is a tedious work. In addition, analyzing these huge numbers of applications manually might result into biased and erroneous output which may eventually cause problems for the companies. If these pools of resumes can be analyzed automatically and presented to the employers in a systematic way for choosing the appropriate person for their company, it may help the applicants and the employers as well. So in order to solve this need, we have developed a framework that takes the resume of the candidates, pull out information from them by recognizing the named entities using machine learning and score the applicants according to some predefined rules and employer requirements. Furthermore, employers can select the best suited candidates for their jobs from these scores by using skyline filtering.

Keywords: Information extraction; named entity recognition; machine learning; skyline queries

Farzana Yasmin, Mohammad Imtiaz Nur and Mohammad Shamsul Arefin, “Developing a Framework for Potential Candidate Selection” International Journal of Advanced Computer Science and Applications(IJACSA), 10(12), 2019. http://dx.doi.org/10.14569/IJACSA.2019.0101245

@article{Yasmin2019,
title = {Developing a Framework for Potential Candidate Selection},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2019.0101245},
url = {http://dx.doi.org/10.14569/IJACSA.2019.0101245},
year = {2019},
publisher = {The Science and Information Organization},
volume = {10},
number = {12},
author = {Farzana Yasmin and Mohammad Imtiaz Nur and Mohammad Shamsul Arefin}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

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