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  Mining frequent itemsets in evolving databases (2002) [22 citations — 11 self]

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by A. A. Veloso, S. Parthasarathy
In Proc. of the 2 nd SIAM Int'l Conf. on Data Mining
http://www.cis.ohio-state.edu/~srini/papers/siam02.ps
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Abstract:

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Citations

1607 Fast algorithms for mining association rules – Agrawal, Srikant - 1994
1449 Mining association rules between sets of items in large databases – Agrawal, Imielinski, et al. - 1993
342 Dynamic itemset counting and implication rules for market basket data – Brin, Motwani, et al. - 1997
252 Efficiently mining long patterns from databases – Bayardo - 1998
194 New Algorithms for fast discovery of association rules – Zaki, Ogihara, et al. - 1997
147 Maintenance of discovered association rules in large databases: an 356 incremental updating technique – Cheung, Han, et al. - 1996
140 Levelwise search and borders of theories in knowledge discovery – Mannila, Toivonen - 1997
82 Efficiently Mining Maximal Frequent Itemsets – Gouda, Zaki - 2001
57 An Efficient Algorithm for the Incre-mental Updation of Association Rules – Thomas, Bodagala, et al.
37 Efficient algorithms for discovering frequent sets in incremental databases – Feldman, Aumann, et al. - 1997
12 ChARM: An Ecient Algorithm for Closed association Rule Mining – Zaki, Hsiao - 1999
10 Analyzing the interestingness of association rules from the temporal dimension – Liu, Ma, et al. - 2001
9 Incremental Mining of Constrained Associations – Thomas, Chakravarthy - 2000
8 An efficient algorithm to update large itemsets with early pruning – Ayan, Tansel, et al. - 1999
2 A General Incremental Technique for Maitaining Discovered Association Rules – Cheung, Lee, et al. - 1997
2 Maintenance of Association Rules: When to Update – Lee, Cheung - 1997