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» Scaling Clustering Algorithms to Large Databases
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SIGMOD
2000
ACM
165views Database» more  SIGMOD 2000»
14 years 26 days ago
Finding Generalized Projected Clusters In High Dimensional Spaces
High dimensional data has always been a challenge for clustering algorithms because of the inherent sparsity of the points. Recent research results indicate that in high dimension...
Charu C. Aggarwal, Philip S. Yu
BMCBI
2007
177views more  BMCBI 2007»
13 years 8 months ago
The BioPrompt-box: an ontology-based clustering tool for searching in biological databases
Background: High-throughput molecular biology provides new data at an incredible rate, so that the increase in the size of biological databanks is enormous and very rapid. This sc...
Claudio Corsi, Paolo Ferragina, Roberto Marangoni
BMCBI
2010
149views more  BMCBI 2010»
13 years 8 months ago
KID - an algorithm for fast and efficient text mining used to automatically generate a database containing kinetic information o
Background: The amount of available biological information is rapidly increasing and the focus of biological research has moved from single components to networks and even larger ...
Stephanie Heinen, Bernhard Thielen, Dietmar Schomb...
EMNLP
2008
13 years 10 months ago
Scalable Language Processing Algorithms for the Masses: A Case Study in Computing Word Co-occurrence Matrices with MapReduce
This paper explores the challenge of scaling up language processing algorithms to increasingly large datasets. While cluster computing has been available in commercial environment...
Jimmy J. Lin
CLUSTER
2000
IEEE
14 years 28 days ago
Contention-free Complete Exchange Algorithm on Clusters
To construct a large commodity clustec a hierarchical network is generally adopted for connecting the host muchines, where a Gigabit backbone switch connects a few commodity switc...
Anthony T. C. Tam, Cho-Li Wang