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: 3566
Venue: SIGMOD
Year: 2004
Pagerank: 4.1945683e-05
Overall Rank: 12,575 | 12.52%
DOI: -

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Authors

1. Panagiotis G. Ipeirotis
2. Luis Gravano

Incoming Citations (Sorted by Pagerank)

Showing 0 of 0 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank

Outgoing Citations (Sorted by Pagerank)

Showing 5 of 5 cited papers.

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

Rank	Cited Paper	Year	Venue	Pagerank
1,033	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
1,492	Distributed Search over the Hidden Web: Hierarchical Database Sampling and Selection	2002	VLDB	0.00011694396
3,734	STARTS: Stanford Proposal for Internet Meta-Searching	1997	SIGMOD	6.8095787e-05
6,927	Database Selection Using Actual Physical and Acquired Logical Collection Resources in a Massive Domain-specific Operational Environment	2002	VLDB	4.8925595e-05

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