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Automatic Discovery of Language Models for Text Databases

Summary: DB selection service builds language models for text databases by sampling query results, removing the need for database-provided models. Carefully chosen queries approximate sampling, yielding accurate models from few queries and documents for GlOSS-driven cross-database discovery. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
3185
Venue
SIGMOD
Year
1999
Pagerank
0.00010239819
Overall Rank
1,601 | 89.02%
DOI
10.1145/304182.304224

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{callan_sigmod99,
        title = {{Automatic Discovery of Language Models for Text Databases}},
        author = {Callan, Jamie and Connell, Margaret and Du, Aiqun},
        series = {{SIGMOD} '99},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/304182.304224},
        url = {https://dl.acm.org/doi/10.1145/304182.304224},
        year = {1999}
}

Incoming Citations (Sorted by Pagerank)

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Outgoing Citations (Sorted by Pagerank)

Showing 3 of 3 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank Cited Paper Year Venue Pagerank
2,016 Generalizing GlOSS to Vector-Space Databases and Broker Hierarchies 1995 VLDB 9.3030756e-05
4,022 The Effectiveness of GLOSS for the Text Database Discovery Problem 1994 SIGMOD 6.9498405e-05
5,013 STARTS: Stanford Proposal for Internet Meta-Searching 1997 SIGMOD 6.4005976e-05
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