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» Large Scale Data Mining: Challenges and Responses
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DEBS
2009
ACM
15 years 9 months ago
Event-based systems: opportunities and challenges at exascale
Streaming data models have been shown to be useful in many applications requiring high-performance data exchange. Application-level overlay networks are a natural way to realize t...
Greg Eisenhauer, Matthew Wolf, Hasan Abbasi, Karst...
JDWM
2006
178views more  JDWM 2006»
15 years 6 months ago
Improved Data Partitioning for Building Large ROLAP Data Cubes in Parallel
The pre-computation of data cubes is critical to improving the response time of On-Line Analytical Processing (OLAP) systems and can be instrumental in accelerating data mining ta...
Ying Chen, Frank K. H. A. Dehne, Todd Eavis, Andre...
KDD
2008
ACM
165views Data Mining» more  KDD 2008»
16 years 6 months ago
Colibri: fast mining of large static and dynamic graphs
Low-rank approximations of the adjacency matrix of a graph are essential in finding patterns (such as communities) and detecting anomalies. Additionally, it is desirable to track ...
Hanghang Tong, Spiros Papadimitriou, Jimeng Sun, P...
ICDM
2002
IEEE
159views Data Mining» more  ICDM 2002»
15 years 11 months ago
O-Cluster: Scalable Clustering of Large High Dimensional Data Sets
Clustering large data sets of high dimensionality has always been a serious challenge for clustering algorithms. Many recently developed clustering algorithms have attempted to ad...
Boriana L. Milenova, Marcos M. Campos
IDA
2011
Springer
15 years 1 months ago
A parallel, distributed algorithm for relational frequent pattern discovery from very large data sets
The amount of data produced by ubiquitous computing applications is quickly growing, due to the pervasive presence of small devices endowed with sensing, computing and communicatio...
Annalisa Appice, Michelangelo Ceci, Antonio Turi, ...