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ColumbuScout: Towards Building Local Search Engines over Large Databases

Summary: ColumbuScout demonstrates a local search engine over large databases, replacing form-based SQL translations with search-engine-like queries and ranking. It introduces novel indexing and storage designs to boost efficiency and scalability, and is easy for developers to deploy over existing databases. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
h67342db292bd6035
Venue
SIGMOD
Year
2012
Pagerank
4.9605343e-05
Overall Rank
12,653 | 15.19%
DOI
10.1145/2213836.2213914

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Authors

BibTeX Citation

@inproceedings{hansen_sigmod12,
        title = {{ColumbuScout: Towards Building Local Search Engines over Large Databases}},
        author = {Hansen, Cody and Li, Feifei},
        series = {{SIGMOD} '12},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/2213836.2213914},
        url = {https://dl.acm.org/doi/10.1145/2213836.2213914},
        year = {2012}
}

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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
217 Efficient IR-Style Keyword Search over Relational Databases 2003 VLDB 0.00024417824
1,963 DBXplorer: Enabling Keyword Search over Relational Databases 2002 SIGMOD 9.2838424e-05
3,323 Keyword Search on Structured and Semi-Structured Data 2009 SIGMOD 7.4116032e-05
5,811 Efficient Approximate Search on String Collections (Tutorial) 2009 VLDB 5.9701598e-05
8,469 Seaform: Search-As-You-Type in Forms 2010 VLDB 5.3148581e-05
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