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» An Extension to SQL for Mining Association Rules
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KDD
2002
ACM
173views Data Mining» more  KDD 2002»
14 years 8 months ago
LumberJack: Intelligent Discovery and Analysis of Web User Traffic Composition
Web Usage Mining enables new understanding of user goals on the Web. This understanding has broad applications, and traditional mining techniques such as association rules have bee...
Ed Huai-hsin Chi, Adam Rosien, Jeffrey Heer
KDD
2006
ACM
198views Data Mining» more  KDD 2006»
14 years 8 months ago
CFI-Stream: mining closed frequent itemsets in data streams
Mining frequent closed itemsets provides complete and condensed information for non-redundant association rules generation. Extensive studies have been done on mining frequent clo...
Nan Jiang, Le Gruenwald
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
SP
1999
IEEE
184views Security Privacy» more  SP 1999»
13 years 12 months ago
A Data Mining Framework for Building Intrusion Detection Models
There is often the need to update an installed Intrusion Detection System (IDS) due to new attack methods or upgraded computing environments. Since many current IDSs are construct...
Wenke Lee, Salvatore J. Stolfo, Kui W. Mok
GIS
2006
ACM
14 years 8 months ago
Mining frequent geographic patterns with knowledge constraints
The large amount of patterns generated by frequent pattern mining algorithms has been extensively addressed in the last few years. In geographic pattern mining, besides the large ...
Luis Otávio Alvares, Paulo Martins Engel, S...