Abstract
In modern days people search job opportunities or candidates mainly online, where several websites for this purpose already do exist (LinkedIn, Guru and Freelancer, to name a few). This task is especially difficult because of the large number of items to look for and the need for manual compatibility by human resources. What we propose in this paper is an architecture for recruitment matchmaking that considers the user and opportunity models (content-based filtering) and social interactions (collaborative filtering) to improve the quality of its recommendations. This solution is also able to generate adequate teams for a given job opportunity, based not only on the needed competences but also on the social compatibility between their members, both using user-generated content and automatic platform data. This article is the extended version of ICE-B’s Hyred - HYbrid Job REcommenDation System, which means that it includes updated information and new advances, especially in Chap. 5.
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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. (2016). ARM: Architecture for Recruitment Matchmaking. In: Obaidat, M., Lorenz, P. (eds) E-Business and Telecommunications. ICETE 2015. Communications in Computer and Information Science, vol 585. Springer, Cham. https://doi.org/10.1007/978-3-319-30222-5_4
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DOI: https://doi.org/10.1007/978-3-319-30222-5_4
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