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Matching, Learning and Querying in the HR domain

In recent times, the field of human resources management and e-recruitment has been revolutionized by the emergence of new techniques and tools that allow to automate most of the traditional processes of the sector (matching job offers and profile candidates, learning the features of each business sector, querying information, and so on). The truth is that these new methods bring many advantages, among which we can highlight the support to decision making and the permanent monitoring and evaluation of these processes.

In this context, two main types of techniques stand out. Those based on deep learning and those inspired by knowledge-based approaches. The former are fast, effective and usually give very good results. However, they lack interpretability, that is, the ability for a human operator to understand them easily. Knowledge-based approaches, on the other hand, although they are not usually so fast and effective, are highly interpretable. This means that a human operator can understand them much more easily.
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