A Neural Information Retrieval Approach for Résumé Searching in a Recruitment Agency

Brandon Grech, David Suda

2020

Abstract

Finding résumés that match a job description can be a daunting task for a recruitment agency, due to the fact that these agencies are dealing with hundreds of job descriptions and tens of thousands of résumés simultaneously. In this paper we explain a search method devised for a recruitment agency by measuring similarity between résumé documents and job description documents. Document vectors are obtained via TF-IDF weights from word embeddings arising from a neural language model with a skip-gram loss function. We show that, with this approach, successful searches can be achieved, and that the number of skips assumed in the skip gram loss function determines how successful it can be for different job descriptions.

Paper Citation

in Harvard Style

Grech B. and Suda D. (2020). A Neural Information Retrieval Approach for Résumé Searching in a Recruitment Agency. In Proceedings of the 9th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM, ISBN 978-989-758-397-1, pages 645-651. DOI: 10.5220/0009355006450651

in Bibtex Style

@conference{icpram20,
author={Brandon Grech and David Suda},
title={A Neural Information Retrieval Approach for Résumé Searching in a Recruitment Agency},
booktitle={Proceedings of the 9th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,},
year={2020},
pages={645-651},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0009355006450651},
isbn={978-989-758-397-1},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 9th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,
TI - A Neural Information Retrieval Approach for Résumé Searching in a Recruitment Agency
SN - 978-989-758-397-1
AU - Grech B.
AU - Suda D.
PY - 2020
SP - 645
EP - 651
DO - 10.5220/0009355006450651