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ICEIS
2009
IEEE
14 years 2 months ago
NARFO Algorithm: Mining Non-redundant and Generalized Association Rules Based on Fuzzy Ontologies
Traditional approaches for mining generalized association rules are based only on database contents, and focus on exact matches among items. However, in many applications, the use ...
Rafael Garcia Miani, Cristiane A. Yaguinuma, Maril...
KDD
2003
ACM
194views Data Mining» more  KDD 2003»
14 years 8 months ago
Finding recent frequent itemsets adaptively over online data streams
A data stream is a massive unbounded sequence of data elements continuously generated at a rapid rate. Consequently, the knowledge embedded in a data stream is more likely to be c...
Joong Hyuk Chang, Won Suk Lee
CORR
2008
Springer
99views Education» more  CORR 2008»
13 years 7 months ago
A Model-Based Frequency Constraint for Mining Associations from Transaction Data
Mining frequent itemsets is a popular method for finding associated items in databases. For this method, support, the co-occurrence frequency of the items which form an associatio...
Michael Hahsler
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
DKE
2008
124views more  DKE 2008»
13 years 7 months ago
A MaxMin approach for hiding frequent itemsets
In this paper, we are proposing a new algorithmic approach for sanitizing raw data from sensitive knowledge in the context of mining of association rules. The new approach (a) rel...
George V. Moustakides, Vassilios S. Verykios