Abstract
Data provenance can support the understanding and debugging of complex data processing pipelines, which are for instance common in data integration scenarios. One task in data integration is entity resolution (ER), i.e., the identification of multiple representations of a same real world entity. This paper focuses of provenance modeling and capture for typical ER tasks. While our definition of ER provenance is independent of the actual language or technology used to define an ER task, the method we implement as a proof of concept instruments ER rules specified in HIL, a high-level data integration language.
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Acknowledgements
The authors thank the German Research Foundation (DFG) for financial support within project D03 of SFB/ Transregio 161. This research was also partly funded by an IBM Faculty Award.
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Oppold, S., Herschel, M. (2018). Provenance for Entity Resolution. In: Belhajjame, K., Gehani, A., Alper, P. (eds) Provenance and Annotation of Data and Processes. IPAW 2018. Lecture Notes in Computer Science(), vol 11017. Springer, Cham. https://doi.org/10.1007/978-3-319-98379-0_25
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DOI: https://doi.org/10.1007/978-3-319-98379-0_25
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