Semint: A System Prototype for Semantic Integration in Heterogeneous Databases
Summary: Semint is a system prototype for semantic integration across heterogeneous databases. It automatically discovers equivalent attributes from source information via pairwise comparisons, removing reliance on hand-crafted mappings. (summarized by gpt-5-nano on Feb 09 2026)
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Authors
- 1. Wen-Syan Li (Northwestern University)
- 2. Chris Clifton (Northwestern University)
BibTeX Citation
@inproceedings{li_sigmod95,
title = {{Semint: A System Prototype for Semantic Integration in Heterogeneous Databases}},
author = {Li, Wen-Syan and Clifton, Chris},
series = {{SIGMOD} '95},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/223784.223897},
url = {https://dl.acm.org/doi/10.1145/223784.223897},
year = {1995}
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| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 3,640 | Semantic Integration in Heterogeneous Databases Using Neural Networks | 1994 | VLDB | 7.2327067e-05 |
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