Integrating and Querying Taxonomies with QUEST in the Presence of Conflicts
Summary: Introduces QUEST, a query-driven system for integrating scientific data and taxonomies amid misalignments and conflicts. A constraint-based data model captures value and structural conflicts and enables context-aware observation and resolution guided by research questions. (summarized by gpt-5-nano on Feb 09 2026)
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Authors
- 1. Yan Qi (Arizona State University)
- 2. K. Selçuk Candan (Arizona State University)
- 3. Maria Luisa Sapino (University of Turin)
- 4. Keith W. Kintigh (Arizona State University)
BibTeX Citation
@inproceedings{qi_sigmod07,
title = {{Integrating and Querying Taxonomies with QUEST in the Presence of Conflicts}},
author = {Qi, Yan and Candan, K. Selçuk and Sapino, Maria Luisa and Kintigh, Keith W.},
series = {{SIGMOD} '07},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/1247480.1247639},
url = {https://dl.acm.org/doi/10.1145/1247480.1247639},
year = {2007}
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Outgoing Citations (Sorted by Pagerank)
Showing 6 of 6 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 78 | ULDBs: Databases with Uncertainty and Lineage | 2006 | VLDB | 0.00036571789 |
| 180 | Schema Mapping as Query Discovery | 2000 | VLDB | 0.00026772368 |
| 297 | Generic Schema Matching with Cupid | 2001 | VLDB | 0.00022157284 |
| 454 | Using Schema Matching to Simplify Heterogeneous Data Translation | 1998 | VLDB | 0.00018133578 |
| 1,733 | Reconciling while Tolerating Disagreement in Collaborative Data Sharing | 2006 | SIGMOD | 9.906536e-05 |
| 6,856 | FICSR: Feedback-based InConSistency Resolution and Query Processing on Misaligned Data Sources | 2007 | SIGMOD | 5.7530103e-05 |
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