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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
3123
Venue
SIGMOD
Year
1999
Pagerank
0.00013777757
Overall Rank
1,131 | 92.14%
DOI
-

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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
1,256 Generalizing GLOSS to Vector-Space Databases and Broker Hierarchies 1995 VLDB 0.00013022726
3,112 The Effectiveness of GLOSS for the Text Database Discovery Problem 1994 SIGMOD 7.5472744e-05
3,734 STARTS: Stanford Proposal for Internet Meta-Searching 1997 SIGMOD 6.8095787e-05
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