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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
8861
Venue
VLDB
Year
2002
Pagerank
0.00011694396
Overall Rank
1,492 | 89.63%
DOI
-

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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
1,033 Determining Text Databases to Search in the Internet 1998 VLDB 0.00014543835
1,131 Automatic Discovery of Language Models for Text Databases 1999 SIGMOD 0.00013777757
3,734 STARTS: Stanford Proposal for Internet Meta-Searching 1997 SIGMOD 6.8095787e-05
3,950 Probe, Count, and Classify: Categorizing Hidden-Web Databases 2001 SIGMOD 6.5953844e-05
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