Abstract
We describe a recruitment support system aiming to help recruiters in finding candidates who are likely to be interested in a given job offer. We present the architecture of that system and explain roles of its main modules. We also give examples of analytical processes supported by the system. In the paper, we focus on a data processing chain that utilizes domain knowledge for the extraction of meaningful features representing pairs of candidates and offers. Moreover, we discuss the usage of a word2vec model for finding concise vector representations of the offers, based on their short textual descriptions. Finally, we present results of an empirical evaluation of our system.
Project co-financed by European Union Funds under the Smart Growth Operational Programme, Sub-programme 2.3.2, Innovation Voucher. Under the project: POIR.02.03.02-14-0009/15 European Fund of Regional Development. Data used in this study was provided by the Toolbox for HR company.
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Notes
- 1.
BIZON is a name of a popular Polish combine harvester. https://en.wikipedia.org/wiki/Bizon_(company).
References
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Acknowledgments
We would like to cordially thank Marcin Smolinski and Anna Czartoszewska-Świerczyńska from Toolbox for HR for cooperation in this project, providing access to the data and supplying us with domain knowledge. We would also like to thank Aleksander Wasiukiewicz and Agnieszka Legut for their administrative support and advise.
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Janusz, A., Stawicki, S., Drewniak, M., Ciebiera, K., Ślęzak, D., Stencel, K. (2018). How to Match Jobs and Candidates - A Recruitment Support System Based on Feature Engineering and Advanced Analytics. In: Medina, J., et al. Information Processing and Management of Uncertainty in Knowledge-Based Systems. Theory and Foundations. IPMU 2018. Communications in Computer and Information Science, vol 854. Springer, Cham. https://doi.org/10.1007/978-3-319-91476-3_42
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