A Graph Method for Keyword-based Selection of the top-K Databases
Summary: G-KS uses a keyword graph to summarize each database and computes DB-query similarity to select top-K candidates for a KS query over multiple DBMSs. Experiments show G-KS outperforms prior methods in precision, recall, efficiency, space, and semantic flexibility. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Quang Hieu Vu (National University of Singapore)
- 2. Beng Chin Ooi (National University of Singapore)
- 3. Dimitris Papadias (Hong Kong University of Science and Technology)
- 4. Anthony K. H. Tung (National University of Singapore)
BibTeX Citation
@inproceedings{vu_sigmod08,
title = {{A Graph Method for Keyword-based Selection of the top-K Databases}},
author = {Vu, Quang Hieu and Ooi, Beng Chin and Papadias, Dimitris and Tung, Anthony K. H.},
series = {{SIGMOD} '08},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/1376616.1376707},
url = {https://dl.acm.org/doi/10.1145/1376616.1376707},
year = {2008}
}
Incoming Citations (Sorted by Pagerank)
Showing 1 of 1 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 3,239 | Keyword Search on Structured and Semi-Structured Data | 2009 | SIGMOD | 7.6078324e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 13 of 13 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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