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Distributed Search over the Hidden Web: Hierarchical Database Sampling and Selection

Summary: Proposes metasearch over hidden-web databases via adaptive probes to produce content summaries with absolute word-frequency estimates. Introduces a hierarchical selection algorithm using these summaries and an induced taxonomy to surpass flat methods, validated on 50 real databases. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
9052
Venue
VLDB
Year
2002
Pagerank
0.00010633832
Overall Rank
1,483 | 89.83%
DOI
10.1016/B978-155860869-6/50042-1

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{ipeirotis_vldb02,
        title = {{Distributed Search over the Hidden Web: Hierarchical Database Sampling and Selection}},
        author = {Ipeirotis, Panagiotis G. and Gravano, Luis},
        journal = {PVLDB},
        series = {{VLDB} '02},
        doi = {10.1016/B978-155860869-6/50042-1},
        url = {https://doi.org/10.1016/B978-155860869-6/50042-1},
        year = {2002}
}

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Outgoing Citations (Sorted by Pagerank)

Showing 4 of 4 cited papers.

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

Rank Cited Paper Year Venue Pagerank
1,601 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
4,524 Probe, Count, and Classify: Categorizing Hidden-Web Databases 2001 SIGMOD 6.6457031e-05
5,013 STARTS: Stanford Proposal for Internet Meta-Searching 1997 SIGMOD 6.4005976e-05
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