GeoFlux: Hands-Off Data Integration Leveraging Join Key Knowledge
Summary: Hands-off data integration by auto-identifying geographic join keys for government datasets. GeoFlux's crosswalk algorithm auto-aggregates geographic units across diverse geography types and schemas, enabling fully automatic, user-friendly integration. (summarized by gpt-5-nano on Feb 09 2026)
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Authors
- 1. Jie Song (University of Michigan)
- 2. Danai Koutra (University of Michigan)
- 3. Murali Mani (University of Michigan, Flint)
- 4. H. V. Jagadish (University of Michigan)
BibTeX Citation
@inproceedings{song_sigmod18,
title = {{GeoFlux: Hands-Off Data Integration Leveraging Join Key Knowledge}},
author = {Song, Jie and Koutra, Danai and Mani, Murali and Jagadish, H. V.},
series = {{SIGMOD} '18},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3183713.3193546},
url = {https://dl.acm.org/doi/10.1145/3183713.3193546},
year = {2018}
}
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Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 390 | COMA - A system for flexible combination of schema matching approaches | 2002 | VLDB | 0.00019382486 |
| 493 | Data Integration for the Relational Web | 2009 | VLDB | 0.00017558709 |
| 1,751 | Sample-Driven Schema Mapping | 2012 | SIGMOD | 9.838446e-05 |
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