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» MapReduce: Simplified Data Processing on Large Clusters
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PKDD
2010
Springer
235views Data Mining» more  PKDD 2010»
13 years 7 months ago
Online Structural Graph Clustering Using Frequent Subgraph Mining
The goal of graph clustering is to partition objects in a graph database into different clusters based on various criteria such as vertex connectivity, neighborhood similarity or t...
Madeleine Seeland, Tobias Girschick, Fabian Buchwa...
IPPS
2003
IEEE
14 years 2 months ago
Design and Evaluation of a Parallel HOP Clustering Algorithm for Cosmological Simulation
Clustering, or unsupervised classification, has many uses in fields that depend on grouping results from large amount of data, an example being the N-body cosmological simulation ...
Ying Liu, Wei-keng Liao, Alok N. Choudhary
BMCBI
2005
112views more  BMCBI 2005»
13 years 9 months ago
Visualization methods for statistical analysis of microarray clusters
Background: The most common method of identifying groups of functionally related genes in microarray data is to apply a clustering algorithm. However, it is impossible to determin...
Matthew A. Hibbs, Nathaniel C. Dirksen, Kai Li, Ol...
SIGMOD
2010
ACM
207views Database» more  SIGMOD 2010»
14 years 1 months ago
Automatic contention detection and amelioration for data-intensive operations
To take full advantage of the parallelism offered by a multicore machine, one must write parallel code. Writing parallel code is difficult. Even when one writes correct code, the...
John Cieslewicz, Kenneth A. Ross, Kyoho Satsumi, Y...
NAACL
2007
13 years 10 months ago
Unsupervised Natural Language Processing Using Graph Models
In the past, NLP has always been based on the explicit or implicit use of linguistic knowledge. In classical computer linguistic applications explicit rule based approaches prevai...
Chris Biemann