Developing a Framework for Potential Candidate Selection

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.

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