International Conference on Operations Research and Enterprise Systems (ICORES 2020)
This website contains information related to a paper that is "under review" in ICORES 2020 scientific conference.
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The code for the paper is available at https://github.com/nkanak/icores-2020.
The dataset used in the experiments is available here.
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.
Natural Language Processing, Machine Learning, Operations Research, Human Resource Allocation, Linear Assignment Problem