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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
10114
Venue
VLDB
Year
2010
Pagerank
4.6330652e-05
Overall Rank
7,844 | 45.49%
DOI
-

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Incoming Citations (Sorted by Pagerank)

Showing 2 of 2 citing papers.

Rank Citing Paper Year Venue Pagerank
2,729 String Similarity Joins: An Experimental Evaluation 2014 VLDB 8.2175463e-05
11,912 Indexing Metric Uncertain Data for Range Queries 2015 SIGMOD 4.1905499e-05
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Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

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