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Mining Compressed Frequent-Pattern Sets

Summary: Addresses explosive growth of frequent-pattern outputs by compressing sets with delta-clusters and selecting a cluster representative. Proposes two greedy algorithms: RPglobal (guaranteed compression bound, higher cost) and RPlocal (faster, looser bounds; faster than FPClose); both reduce closed patterns by almost two orders of magnitude and enable a tunable quality-efficiency trade-off when combined. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
9349
Venue
VLDB
Year
2005
Pagerank
7.6448739e-05
Overall Rank
3,055 | 78.75%
DOI
-

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