Job Offers Classifier using Neural Networks and Oversampling Methods

@article{Ortiz2022JobOC,
  title={Job Offers Classifier using Neural Networks and Oversampling Methods},
  author={Germ{\'a}n Ortiz and Gemma Bel Enguix and Helena G{\'o}mez-Adorno and Iqra Ameer and Grigori Sidorov},
  journal={ArXiv},
  year={2022},
  volume={abs/2207.06223}
}
. Both policy and research benefit from a better understand-ing of individuals’ jobs. However, as large-scale administrative records are increasingly employed to represent labor market activity, new automatic methods to classify jobs will become necessary. We developed an automatic job offers classifier using a dataset collected from the largest job bank of Mexico known as Bumeran 5 . We applied machine learning algorithms such as Support Vector Machines, Naive-Bayes, Logistic Regression, Random… 
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