Database Paper Browser

Back to papers

An Efficient Rigorous Approach for Identifying Statistically Significant Frequent Itemsets

Summary: Apply Chen–Stein Poisson approximation to the count of itemsets with support ≥ s to locate s* where observed counts exceed random-data expectations. Presents an efficient parametric multi-hypothesis test controlling FDR using whole-dataset counts rather than per-itemset tests; empirically validated. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID
1483
Venue
PODS
Year
2009
Pagerank
5.8925807e-05
Overall Rank
4,829 | 66.41%
DOI
-

Incoming Non-self Citations Over Time

Authors

Incoming Citations (Sorted by Pagerank)

Showing 3 of 3 citing papers.

Rank Citing Paper Year Venue Pagerank
1,940 SliceLine: Fast, Linear-Algebra-based Slice Finding for ML Model Debugging 2021 SIGMOD 0.00010020173
2,930 Assessing and Ranking Structural Correlations in Graphs 2011 SIGMOD 7.8723983e-05
12,132 Controlling False Positives in Association Rule Mining 2012 VLDB 4.1945683e-05
Previous Page 1 / 1 Next

Outgoing Citations (Sorted by Pagerank)

Showing 4 of 4 cited papers.

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

Rank Cited Paper Year Venue Pagerank
13 Mining Association Rules between Sets of Items in Large Databases 1993 SIGMOD 0.0010864752
599 Mining Quantitative Association Rules in Large Relational Tables 1996 SIGMOD 0.00019394214
3,055 Mining Compressed Frequent-Pattern Sets 2005 VLDB 7.6448739e-05
5,565 A New Framework For Itemset Generation 1998 PODS 5.4318211e-05
Previous Page 1 / 1 Next

Semantically Similar Papers