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)
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Authors
- 1. Guimei Liu
- 2. Andre Suchitra
- 3. Limsoon Wong
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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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