Abstract
Volunteering is an omnipresent cornerstone of our society. Currently, new forms of volunteering like crowd workers, engagement hoppers or patchwork volunteers are arising. This next-generation volunteers more than ever demand for volunteering marketplaces providing adequate MatchMaking capabilities. This paper proposes a semantic MatchMaking framework allowing to compute a ranked list of tasks or volunteers whose profiles match “as closely as possible”. For this, an ontology-based vocabulary is established which explicitly captures the multifaceted nature of profiles for both, tasks and volunteers. Each of these facets is associated with adequate similarity measures and meta information explicitly capturing domain expertise. The feasibility of the approach is demonstrated by a simple example and a first prototype.
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Schönböck, J. et al. (2018). A Semantic MatchMaking Framework for Volunteering MarketPlaces. In: Rocha, Á., Adeli, H., Reis, L.P., Costanzo, S. (eds) Trends and Advances in Information Systems and Technologies. WorldCIST'18 2018. Advances in Intelligent Systems and Computing, vol 745. Springer, Cham. https://doi.org/10.1007/978-3-319-77703-0_70
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DOI: https://doi.org/10.1007/978-3-319-77703-0_70
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