SPARK: Top-k Keyword Query in Relational Databases
Summary: Introduces SPARK for top-k keyword queries over relational data using a virtual-document ranking that adapts IR techniques. Proposes efficient processing with minimal DB accesses; shows strong effectiveness and efficiency on large real datasets across two RDBMS. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Yi Luo (University of New South Wales)
- 2. Xuemin Lin (University of New South Wales)
- 3. Wei Wang (University of New South Wales)
- 4. Xiaofang Zhou (University of Queensland)
BibTeX Citation
@inproceedings{luo_sigmod07,
title = {{SPARK: Top-k Keyword Query in Relational Databases}},
author = {Luo, Yi and Lin, Xuemin and Wang, Wei and Zhou, Xiaofang},
series = {{SIGMOD} '07},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/1247480.1247495},
url = {https://dl.acm.org/doi/10.1145/1247480.1247495},
year = {2007}
}
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