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PAKDD
2005
ACM
124views Data Mining» more  PAKDD 2005»
14 years 1 months ago
Finding Sporadic Rules Using Apriori-Inverse
We define sporadic rules as those with low support but high confidence: for example, a rare association of two symptoms indicating a rare disease. To find such rules using the w...
Yun Sing Koh, Nathan Rountree
AI
2001
Springer
14 years 11 days ago
A Low-Scan Incremental Association Rule Maintenance Method Based on the Apriori Property
As new transactions update data sources and subsequently the data warehouse, the previously discovered association rules in the old database may no longer be interesting rules in ...
Zequn Zhou, C. I. Ezeife
COMPSAC
2005
IEEE
13 years 9 months ago
A Novel Method for Protecting Sensitive Knowledge in Association Rules Mining
Discovering frequent patterns from huge amounts of data is one of the most studied problems in data mining. However, some sensitive patterns with security policies may cause a thr...
En Tzu Wang, Guanling Lee, Yu Tzu Lin
ICDM
2006
IEEE
130views Data Mining» more  ICDM 2006»
14 years 1 months ago
A Framework for Regional Association Rule Mining in Spatial Datasets
The immense explosion of geographically referenced data calls for efficient discovery of spatial knowledge. One critical requirement for spatial data mining is the capability to ...
Wei Ding 0003, Christoph F. Eick, Jing Wang 0007, ...
ISCC
2002
IEEE
147views Communications» more  ISCC 2002»
14 years 23 days ago
A new method for finding generalized frequent itemsets in generalized association rule mining
Generalized association rule mining is an extension of traditional association rule mining to discover more informative rules, given a taxonomy. In this paper, we describe a forma...
Kritsada Sriphaew, Thanaruk Theeramunkong