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On the Discovery of Interesting Patterns in Association Rules

Summary: Introduces calendar algebra to express temporal patterns in association rules and defines calendric rules aligned to user time expressions. Proposes discovery algorithms and optimizations, with results showing 5%-250% speedups over naive approaches. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
8503
Venue
VLDB
Year
1998
Pagerank
4.9272477e-05
Overall Rank
6,782 | 52.82%
DOI
-

Incoming Non-self Citations Over Time

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Incoming Citations (Sorted by Pagerank)

Showing 2 of 2 citing papers.

Rank Citing Paper Year Venue Pagerank
4,919 Optimization of Constrained Frequent Set Queries with 2-variable Constraints 1999 SIGMOD 5.8256934e-05
12,522 Mining Frequent Closed Cubes in 3D Datasets 2006 VLDB 4.1945683e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 7 of 7 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

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