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Determining Text Databases to Search in the Internet

Summary: Predict usefulness of text databases for a query as the count of sufficiently similar documents. Proposes threshold-determination techniques for local databases in a collection-fusion setting with heterogeneous similarity functions. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
8473
Venue
VLDB
Year
1998
Pagerank
0.00014543835
Overall Rank
1,033 | 92.82%
DOI
-

Incoming Non-self Citations Over Time

Authors

Incoming Citations (Sorted by Pagerank)

Showing 8 of 8 citing papers.

Rank Citing Paper Year Venue Pagerank
805 Evaluating Top-k Selection Queries 1999 VLDB 0.00016437265
1,431 Computing Geographical Scopes of Web Resources 2000 VLDB 0.00012021056
1,492 Distributed Search over the Hidden Web: Hierarchical Database Sampling and Selection 2002 VLDB 0.00011694396
2,095 Knocking the Door to the Deep Web: Integrating Web Query Interfaces 2004 SIGMOD 9.5505068e-05
3,950 Probe, Count, and Classify: Categorizing Hidden-Web Databases 2001 SIGMOD 6.5953844e-05
8,691 Efficient and Effective Metasearch for Text Databases Incorporating Linkages among Documents 2001 SIGMOD 4.466355e-05
12,447 AllInOneNews: Development and Evaluation of a Large-Scale News Metasearch Engine 2007 SIGMOD 4.1945683e-05
12,575 When one Sample is not Enough: Improving Text Database Selection Using Shrinkage 2004 SIGMOD 4.1945683e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 2 of 2 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
1,899 Merging Ranks from Heterogeneous Internet Sources 1997 VLDB 0.00010170921
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