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Beyond Itemsets: Mining Frequent Featuresets over Structured Items

Summary: Extends frequent itemset mining to structured items by using per-item feature sets and mining frequent featuresets from user sessions. Proposes a featureset-uncertainty model with probabilistic featuresets learned by constrained least squares, plus diverse mining algorithms and experimental evaluation. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
11140
Venue
VLDB
Year
2015
Pagerank
4.1945683e-05
Overall Rank
11,952 | 16.86%
DOI
-

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Showing 6 of 6 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
36 Fast Algorithms for Mining Association Rules 1994 VLDB 0.00076161096
101 ULDBs: Databases with Uncertainty and Lineage 2006 VLDB 0.0004955674
473 Sampling Large Databases for Association Rules 1996 VLDB 0.0002233798
5,796 Finding Frequent Items in Probabilistic Data 2008 SIGMOD 5.3240234e-05
7,633 Mining Frequent Itemsets over Uncertain Databases 2012 VLDB 4.6914549e-05
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