On the Exploitation of Textual Descriptions for a Better-informed Task Assignment Process
Nikos Kanakaris, Nikos Karacapilidis, Georgios Kournetas
2020
Abstract
Human resources always play a crucial role on firms’ profitability and sustainability. For a long time already, the identification of the appropriate personnel possessing the skills and expertise required to undertake a task is mainly performed through simple keyword searches exploiting structured data. In this paper, we build on Natural Language Processing techniques to take this identification to a higher level of detail, granularity and accuracy. Our approach elaborates unstructured data such as descriptions and titles of tasks to extract valuable information about the employees’ capability of successfully engaging with a particular task. Text classifiers such as naive Bayes, logistic regression, support vector machines, k-nearest neighbors and neural networks are being tested and comparably assessed.
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in Harvard Style
Kanakaris N., Karacapilidis N. and Kournetas G. (2020). On the Exploitation of Textual Descriptions for a Better-informed Task Assignment Process. In Proceedings of the 9th International Conference on Operations Research and Enterprise Systems - Volume 1: ICORES, ISBN 978-989-758-396-4, pages 304-310. DOI: 10.5220/0009151603040310
in Bibtex Style
@conference{icores20,
author={Nikos Kanakaris and Nikos Karacapilidis and Georgios Kournetas},
title={On the Exploitation of Textual Descriptions for a Better-informed Task Assignment Process},
booktitle={Proceedings of the 9th International Conference on Operations Research and Enterprise Systems - Volume 1: ICORES,},
year={2020},
pages={304-310},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0009151603040310},
isbn={978-989-758-396-4},
}
in EndNote Style
TY - CONF
JO - Proceedings of the 9th International Conference on Operations Research and Enterprise Systems - Volume 1: ICORES,
TI - On the Exploitation of Textual Descriptions for a Better-informed Task Assignment Process
SN - 978-989-758-396-4
AU - Kanakaris N.
AU - Karacapilidis N.
AU - Kournetas G.
PY - 2020
SP - 304
EP - 310
DO - 10.5220/0009151603040310