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ICDM
2003
IEEE
140views Data Mining» more  ICDM 2003»
15 years 3 months ago
Mining Frequent Itemsets in Distributed and Dynamic Databases
Traditional methods for frequent itemset mining typically assume that data is centralized and static. Such methods impose excessive communication overhead when data is distributed...
Matthew Eric Otey, Chao Wang, Srinivasan Parthasar...
SIGIR
2011
ACM
14 years 24 days ago
Mining tags using social endorsement networks
Entities on social systems, such as users on Twitter, and images on Flickr, are at the core of many interesting applications: they can be ranked in search results, recommended to ...
Theodoros Lappas, Kunal Punera, Tamás Sarlo...
HPCC
2007
Springer
15 years 4 months ago
An Adaptive Parallel Hierarchical Clustering Algorithm
Clustering of data has numerous applications and has been studied extensively. It is very important in Bioinformatics and data mining. Though many parallel algorithms have been des...
Zhaopeng Li, Kenli Li, Degui Xiao, Lei Yang
KDD
1999
ACM
104views Data Mining» more  KDD 1999»
15 years 2 months ago
Learning Rules from Distributed Data
In this paper a concern about the accuracy (as a function of parallelism) of a certain class of distributed learning algorithms is raised, and one proposed improvement is illustrat...
Lawrence O. Hall, Nitesh V. Chawla, Kevin W. Bowye...
IPPS
2007
IEEE
15 years 4 months ago
Scalable Distributed Execution Environment for Large Data Visualization
To use heterogeneous and geographically distributed resources as a platform for parallel visualization is an intriguing topic of research. This is because of the immense potential...
Micah Beck, Huadong Liu, Jian Huang, Terry Moore