Mining Frequent Patterns without Candidate Generation
Summary: Proposes FP-tree, a compact prefix-tree that compresses frequent-pattern data and eliminates candidate generation. FP-growth mines all patterns via pattern fragment growth and divide-and-conquer on conditional databases, cutting scans and outperforming Apriori by roughly tenfold. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Jiawei Han
- 2. Jian Pei
- 3. Yiwen Yin
Incoming Citations (Sorted by Pagerank)
Showing 13 of 63 citing papers.
Outgoing Citations (Sorted by Pagerank)
Showing 8 of 8 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 36 | Fast Algorithms for Mining Association Rules | 1994 | VLDB | 0.00076161096 |
| 117 | An Effective Hash-Based Algorithm for Mining Association Rules | 1995 | SIGMOD | 0.00045896865 |
| 547 | An Efficient Algorithm for Mining Association Rules in Large Databases | 1995 | VLDB | 0.00020420717 |
| 744 | Beyond Market Baskets: Generalizing Association Rules to Correlations | 1997 | SIGMOD | 0.00017333019 |
| 840 | Efficiently Mining Long Patterns from Databases | 1998 | SIGMOD | 0.00016058396 |
| 904 | Integrating Association Rule Mining with Relational Database Systems: Alternatives and Implications | 1998 | SIGMOD | 0.00015469655 |
| 1,623 | Scalable Techniques for Mining Causal Structures | 1998 | VLDB | 0.00011102927 |
| 1,626 | Exploratory Mining and Pruning Optimizations of Constrained Association Rules | 1998 | SIGMOD | 0.00011094469 |
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