Database Paper Browser

Back to papers

Density Biased Sampling: An Improved Method for Data Mining and Clustering

Summary: Density biased sampling under-samples dense regions and over-samples sparse ones, preserving original densities with weighted samples. Single-pass, memory-efficient algorithm; uniform sampling is a special case, with up to 6× gains on Zipf-like clusters for mining and clustering. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
3176
Venue
SIGMOD
Year
2000
Pagerank
6.3768049e-05
Overall Rank
4,177 | 70.98%
DOI
-

Incoming Non-self Citations Over Time

Authors

Incoming Citations (Sorted by Pagerank)

Showing 5 of 5 citing papers.

Rank Citing Paper Year Venue Pagerank
2,403 Maintaining Variance and k–Medians over Data Stream Windows 2003 PODS 8.8738166e-05
2,807 Optimal Sampling from Sliding Windows 2009 PODS 8.096649e-05
3,651 Using Trees to Depict a Forest 2009 VLDB 6.8727613e-05
6,892 C2P: Clustering based on Closest Pairs 2001 VLDB 4.8889412e-05
7,760 Dscaler: Synthetically Scaling A Given Relational Database 2016 VLDB 4.6548456e-05
Previous Page 1 / 1 Next

Outgoing Citations (Sorted by Pagerank)

Showing 8 of 8 cited papers.

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

Previous Page 1 / 1 Next

Semantically Similar Papers