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Probe, Count, and Classify: Categorizing Hidden-Web Databases

Summary: Automates hidden-web database categorization with a small set of query probes; uses per-probe match counts, no page retrieval. Evaluated on 100+ real databases; achieves low overhead and high accuracy for automatic hierarchical categorization. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
3258
Venue
SIGMOD
Year
2001
Pagerank
6.5953844e-05
Overall Rank
3,950 | 72.53%
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
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