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When one Sample is not Enough: Improving Text Database Selection Using Shrinkage

Summary: Applies shrinkage smoothing to create richer content summaries for text databases, addressing Zipf gaps in samples. Uses hierarchical categorization to borrow vocabularies from related databases and apply shrinkage at query time, improving selection. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
3628
Venue
SIGMOD
Year
2004
Pagerank
5.093636e-05
Overall Rank
12,768 | 12.40%
DOI
10.1145/1007568.1007655

Incoming Non-self Citations Over Time

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Authors

BibTeX Citation

@inproceedings{ipeirotis_sigmod04,
        title = {{When one Sample is not Enough: Improving Text Database Selection Using Shrinkage}},
        author = {Ipeirotis, Panagiotis G. and Gravano, Luis},
        series = {{SIGMOD} '04},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/1007568.1007655},
        url = {https://dl.acm.org/doi/10.1145/1007568.1007655},
        year = {2004}
}

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Outgoing Citations (Sorted by Pagerank)

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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
1,483 Distributed Search over the Hidden Web: Hierarchical Database Sampling and Selection 2002 VLDB 0.00010633832
1,601 Automatic Discovery of Language Models for Text Databases 1999 SIGMOD 0.00010239819
1,625 Determining Text Databases to Search in the Internet 1998 VLDB 0.00010191388
5,013 STARTS: Stanford Proposal for Internet Meta-Searching 1997 SIGMOD 6.4005976e-05
7,531 Database Selection Using Actual Physical and Acquired Logical Collection Resources in a Massive Domain-specific Operational Environment 2002 VLDB 5.6029996e-05
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