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» MapReduce: Simplified Data Processing on Large Clusters
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FLAIRS
2004
13 years 9 months ago
Clustering Spatial Data in the Presence of Obstacles
Clustering is a form of unsupervised machine learning. In this paper, we proposed the DBRS_O method to identify clusters in the presence of intersected obstacles. Without doing an...
Xin Wang, Howard J. Hamilton
ICDM
2010
IEEE
230views Data Mining» more  ICDM 2010»
13 years 5 months ago
Clustering Large Attributed Graphs: An Efficient Incremental Approach
In recent years, many networks have become available for analysis, including social networks, sensor networks, biological networks, etc. Graph clustering has shown its effectivenes...
Yang Zhou, Hong Cheng, Jeffrey Xu Yu
FAST
2007
13 years 9 months ago
Data ONTAP GX: A Scalable Storage Cluster
Data ONTAP GX is a clustered Network Attached File server composed of a number of cooperating filers. Each filer manages its own local file system, which consists of a number of d...
Michael Eisler, Peter Corbett, Michael Kazar, Dani...
PVLDB
2008
182views more  PVLDB 2008»
13 years 7 months ago
SCOPE: easy and efficient parallel processing of massive data sets
Companies providing cloud-scale services have an increasing need to store and analyze massive data sets such as search logs and click streams. For cost and performance reasons, pr...
Ronnie Chaiken, Bob Jenkins, Per-Åke Larson,...
GCB
2003
Springer
105views Biometrics» more  GCB 2003»
14 years 28 days ago
In silico prediction of UTR repeats using clustered EST data
Clustering of EST data is a method for the non-redundant representation of an organisms transcriptome. During clustering of large amounts of EST data, usually some large clusters ...
Stefan A. Rensing, Daniel Lang, Ralf Reski