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A Performance Study of Three Disk-based Structures for Indexing and Querying Frequent Itemsets

Summary: Evaluates three disk-based index structures for frequent itemsets— inverted files, signature files, CFP-tree— with a length-2 itemset pruning technique. Across five containment queries, no universal winner; CFP-tree delivers the strongest overall performance, with dataset-dependent gains. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
10715
Venue
VLDB
Year
2013
Pagerank
4.1945683e-05
Overall Rank
12,095 | 15.86%
DOI
-

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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
181 Mining Frequent Patterns without Candidate Generation 2000 SIGMOD 0.00036992674
978 Rapid Bushy Join-order Optimization with Cartesian Products 1996 SIGMOD 0.00014881073
3,055 Mining Compressed Frequent-Pattern Sets 2005 VLDB 7.6448739e-05
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