Intelligent Agents in the Employment System

: pp. 136 - 141

Olena Slukhaievska, Lyubov Zakhariya

Information Systems and Networks Department, Lviv Polytechnic National University, S. Bandery Str., 12, Lviv, 79013, UKRAINE



The paper considers the project of the system that carries out the bilateral process of search – candidate on a vacancy and automated search of vacancies for a candidate. For this purpose, information on available vacancies through web mining is constantly monitored. The obtained information on new vacancies is classified in terms of information related to previously defined classes of vacancies that play the role of a training sample. The use of algorithms and methods of machine learning allows to increase the efficiency of the selecting suitable work and reducing the search time for candidates for vacancies process.

The proposed approach increases the influence of the individual qualities of recruiters on the process and, consequently, on the result of the job search system by employing tools and methods of artificial intelligence. The system is currently designed for the IT sector, as the most developed in terms of structuring the requirements for candidates and taking into account the large number of proposals in this labor market.

  1. L. Bing. Web Data Mining. Exploring Hyperlinks, Contents, and Usage Data, Second Edition / L. Bing // «Springer». – 2016. – 851 p.
  2. Yaser S. Abu-Mostafa, Malik Magdon-Ismail, Hsuan-Tien Lin. Learning from data / Yaser S. Abu-Mostafa, Malik Magdon-Ismail, Hsuan-Tien Lin // «Williams». – 2015. – 542 p.
  3. Vihar Kurama. Linear Algebra for Deep Learning / Vihar Kurama // Towards Data Science. – 2017. – 1–12 p.
  4. Divyansh Dwivedi. Machine Learning for beginners / Divyansh Dwivedi. // Towards Data Science. – 2016. – 1–7 p.
  5. Amid Fish. Lessons Learned Reproducing a Deep Reinforcement Learning Paper / Amid Fish // Amid Fish. Blog. – 2018. – 1–39 p.
  6. Drew Conway, John Myles White. Machine Learning for Hackers / Drew Conway, John Myles White. // O’Reilly. – 2014. – 746 p.