The DOI matches its Crossref record; 23 of the 23 references it cites were found in a registry or an index.
Evaluation of entity resolution approaches on real-world match problems
Abstract
Despite the huge amount of recent research efforts on entity resolution (matching) there has not yet been a comparative evaluation on the relative effectiveness and efficiency of alternate approaches. We therefore present such an evaluation of existing implementations on challenging real-world match tasks. We consider approaches both with and without using machine learning to find suitable parameterization and combination of similarity functions. In addition to approaches from the research community we also consider a state-of-the-art commercial entity resolution implementation. Our results indicate significant quality and efficiency differences between different approaches. We also find that some challenging resolution tasks such as matching product entities from online shops are not sufficiently solved with conventional approaches based on the similarity of attribute values.
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CrowdER: crowdsourcing entity resolution
Wang, J., Kraska, T., Franklin, M. J., & Feng, J. (2012) · Proceedings of the VLDB Endowment · doi:10.14778/2350229.2350263 · Cited by 507
Deep entity matching with pre-trained language models
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In Search of Big Medical Data Integration Solutions - A Comprehensive Survey
Dhayne, H., Haque, R., Kilany, R., & Taher, Y. (2019) · IEEE Access · doi:10.1109/access.2019.2927491 · Cited by 84
A Survey on Truth Discovery: Concepts, Methods, Applications, and Opportunities
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Metadata
- Authors
- Köpcke, H., Thor, A., & Rahm, E.
- Venue
- Proceedings of the VLDB Endowment
- Published
- 2010-09
- Volume
- 3
- Issue
- 1-2
- Pages
- 484-493
- ISSN
- 2150-8097 (ISSN-L)
- OpenAlex
- W1981590391
- Cited by
- 443
- References
- 23
- FWCI
- 27.03
- Type
- journal article
- Language
- en
- Open access
- closed
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