Abstract
Nowadays people search job opportunities or candidates mainly online, where several websites for this end already do exist (LinkedIn, Freelancer and oDesk, amongst others). This task is especially difficult because of the large number of items to look for and the need for manual compatibility verification. What we propose in this paper is a recruitment recommendation system that considers the user model (content-based filtering) and social interactions (collaborative filtering, e.g. likes and follows) to improve the quality of its suggestions. The devised solution is also able to generate adequate teams for a given job opportunity, based not only on the needed skills but also on the social compatibility between their members.
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Notes
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Virtual Teams - teams that do not work in the same physical space.
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Acknowledgements
This work has been supported by the project WorkInTeam, funded under the Portuguese National Strategic Reference Programme (QREN 2007-2013) under the contract number 2013/38566.
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Coelho, B., Costa, F., Gonçalves, G.M. (2015). HYRE-ME – Hybrid Architecture for Recommendation and Matchmaking in Employment. In: Dregvaite, G., Damasevicius, R. (eds) Information and Software Technologies. ICIST 2015. Communications in Computer and Information Science, vol 538. Springer, Cham. https://doi.org/10.1007/978-3-319-24770-0_19
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DOI: https://doi.org/10.1007/978-3-319-24770-0_19
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