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Entity Matching Meets Data Science: A Progress Report from the Magellan Project

Summary: Magellan treats entity matching as a data-science ecosystem with interoperable tools (PyMatcher, CloudMatcher) for power and lay users. Over 3.5 years, it reports production deployments across 21 EM tasks in 12 companies and a cloud-native, Docker/Kubernetes ecosystem. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
5654
Venue
SIGMOD
Year
2019
Pagerank
4.9408824e-05
Overall Rank
6,747 | 53.07%
DOI
10.1145/3299869.3314042

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Incoming Citations (Sorted by Pagerank)

Showing 2 of 2 citing papers.

Rank Citing Paper Year Venue Pagerank
4,703 Medical Entity Disambiguation Using Graph Neural Networks 2021 SIGMOD 5.9855056e-05
8,099 Sparkly: A Simple yet Surprisingly Strong TF/IDF Blocker for Entity Matching 2023 VLDB 4.5859317e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 7 of 7 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

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