Abstract
We present JedAI, a toolkit for Entity Resolution that can be used in three different ways: as an open-source Java library that implements numerous state-of-the-art, domain-independent methods, as a workbench that facilitates the evaluation of their relative performance and as a desktop application that offers out-of-the-box ER solutions. JedAI bridges the gap between the database and the Semantic Web communities, offering solutions that are applicable to both relational and RDF data. It also conveys a modular architecture that facilitates its extension with more methods and with more comprehensive workflows.
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Acknowledgments
This work has been supported by the project “Your Data Stories”, which is funded by EU Horizon 2020 programme under grant agreement No. 645886. We would also like to thank Oktie Hassanzadeh for sharing with us the implementation in C of the clustering algorithms examined in [3].
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Papadakis, G., Tsekouras, L., Thanos, E., Giannakopoulos, G., Palpanas, T., Koubarakis, M. (2017). JedAI: The Force Behind Entity Resolution. In: Blomqvist, E., Hose, K., Paulheim, H., Ławrynowicz, A., Ciravegna, F., Hartig, O. (eds) The Semantic Web: ESWC 2017 Satellite Events. ESWC 2017. Lecture Notes in Computer Science(), vol 10577. Springer, Cham. https://doi.org/10.1007/978-3-319-70407-4_30
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DOI: https://doi.org/10.1007/978-3-319-70407-4_30
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