Database Paper Browser

Back to papers

Set Similarity Join on Probabilistic Data

Summary: Models probabilistic set data at set- and element-level uncertainty and defines probabilistic set similarity join (PS2J) under possible worlds semantics. Introduces world condensation and pruning techniques—Jaccard distance, probability upper-bound, and aggregate pruning—with indexing and synopses, validated by extensive experiments. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
10113
Venue
VLDB
Year
2010
Pagerank
4.6365272e-05
Overall Rank
7,847 | 45.42%
DOI
-

Incoming Non-self Citations Over Time

Authors

Incoming Citations (Sorted by Pagerank)

Showing 2 of 2 citing papers.

Rank Citing Paper Year Venue Pagerank
2,740 String Similarity Joins: An Experimental Evaluation 2014 VLDB 8.1980628e-05
11,904 Indexing Metric Uncertain Data for Range Queries 2015 SIGMOD 4.1945683e-05
Previous Page 1 / 1 Next

Outgoing Citations (Sorted by Pagerank)

Showing 11 of 11 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