25 search results - page 1 / 5 » Finding recent frequent itemsets adaptively over online data... |
KDD
2003
ACM
14 years 5 months ago
2003
ACM
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...
KDD
2006
ACM
14 years 5 months ago
2006
ACM
Mining frequent closed itemsets provides complete and condensed information for non-redundant association rules generation. Extensive studies have been done on mining frequent clo...
ICDE
2005
IEEE
14 years 5 months ago
2005
IEEE
We consider the problem of maintaining frequency counts for items occurring frequently in the union of multiple distributed data streams. Na?ive methods of combining approximate f...
KAIS
2008
13 years 4 months ago
2008
The increasing prominence of data streams arising in a wide range of advanced applications such as fraud detection and trend learning has led to the study of online mining of freq...
DAWAK
2010
Springer
13 years 5 months ago
2010
Springer
Mining of frequent closed itemsets has been shown to be more efficient than mining frequent itemsets for generating non-redundant association rules. The task is challenging in data...