Sciweavers

2065 search results - page 164 / 413
» Techniques of Cluster Algorithms in Data Mining
Sort
View
HIPC
2009
Springer
15 years 4 months ago
Integrating and optimizing transactional memory in a data mining middleware
As the size of available datasets in various domains is growing rapidly, there is an increasing need for scaling data mining implementations. Coupled with the current trends in co...
Vignesh T. Ravi, Gagan Agrawal
SIGMOD
2004
ACM
209views Database» more  SIGMOD 2004»
16 years 6 months ago
MAIDS: Mining Alarming Incidents from Data Streams
Real-time surveillance systems, network and telecommunication systems, and other dynamic processes often generate tremendous (potentially infinite) volume of stream data. Effectiv...
Y. Dora Cai, David Clutter, Greg Pape, Jiawei Han,...
VLDB
1999
ACM
224views Database» more  VLDB 1999»
15 years 10 months ago
Optimal Grid-Clustering: Towards Breaking the Curse of Dimensionality in High-Dimensional Clustering
Many applications require the clustering of large amounts of high-dimensional data. Most clustering algorithms, however, do not work e ectively and e ciently in highdimensional sp...
Alexander Hinneburg, Daniel A. Keim
CSB
2003
IEEE
150views Bioinformatics» more  CSB 2003»
15 years 11 months ago
Algorithms for Bounded-Error Correlation of High Dimensional Data in Microarray Experiments
The problem of clustering continuous valued data has been well studied in literature. Its application to microarray analysis relies on such algorithms as -means, dimensionality re...
Mehmet Koyutürk, Ananth Grama, Wojciech Szpan...
PKDD
1999
Springer
130views Data Mining» more  PKDD 1999»
15 years 10 months ago
OPTICS-OF: Identifying Local Outliers
: For many KDD applications finding the outliers, i.e. the rare events, is more interesting and useful than finding the common cases, e.g. detecting criminal activities in E-commer...
Markus M. Breunig, Hans-Peter Kriegel, Raymond T. ...