1413 search results - page 30 / 283 » Mining Multiple Large Databases |
FQAS
2004
Springer
13 years 11 months ago
2004
Springer
The discovery of frequently occurring patterns in a time series could be important in several application contexts. As an example, the analysis of frequent patterns in biomedical ...
SDM
2009
SIAM
14 years 4 months ago
2009
SIAM
Current clustering techniques are able to identify arbitrarily shaped clusters in the presence of noise, but depend on carefully chosen model parameters. The choice of model param...
SEKE
2005
Springer
14 years 1 months ago
2005
Springer
The constant increase in use of geographic data in different application domains has resulted in large amounts of data stored in spatial databases and in the desire of data mining....
PARCO
1997
13 years 9 months ago
1997
During the last decade, all commercial database systems have included features for parallel processing into their products. This development has been driven by the fact that datab...
DASFAA
2007
IEEE
2007
IEEE
LAPIN: Effective Sequential Pattern Mining Algorithms by Last Position Induction for Dense Databases
14 years 2 months ago
Sequential pattern mining is very important because it is the basis of many applications. Although there has been a great deal of effort on sequential pattern mining in recent year...