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BMCBI
2008
122views more  BMCBI 2008»
15 years 6 months ago
A practical comparison of two K-Means clustering algorithms
Background: Data clustering is a powerful technique for identifying data with similar characteristics, such as genes with similar expression patterns. However, not all implementat...
Gregory A. Wilkin, Xiuzhen Huang
COMPUTER
1998
131views more  COMPUTER 1998»
15 years 6 months ago
Windows NT Clustering Service
ER ABSTRACTIONS ter service uses several abstractions— including resource, resource dependencies, and resource groups—to simplify both the cluster service itself and user-visib...
Rod Gamache, Rob Short, Mike Massa
EDBT
2010
ACM
155views Database» more  EDBT 2010»
16 years 1 months ago
Reducing metadata complexity for faster table summarization
Since the visualization real estate puts stringent constraints on how much data can be presented to the users at once, table summarization is an essential tool in helping users qu...
K. Selçuk Candan, Mario Cataldi, Maria Luis...
BMCBI
2004
106views more  BMCBI 2004»
15 years 6 months ago
ESTIMA, a tool for EST management in a multi-project environment
Background: Single-pass, partial sequencing of complementary DNA (cDNA) libraries generates thousands of chromatograms that are processed into high quality expressed sequence tags...
Charu G. Kumar, Richard LeDuc, George Gong, Levan ...
EACL
2003
ACL Anthology
15 years 8 months ago
Combining Distributional and Morphological Information for Part of Speech Induction
In this paper we discuss algorithms for clustering words into classes from unlabelled text using unsupervised algorithms, based on distributional and morphological information. We...
Alexander Clark