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KDD
2003
ACM
191views Data Mining» more  KDD 2003»
14 years 9 months ago
Assessment and pruning of hierarchical model based clustering
The goal of clustering is to identify distinct groups in a dataset. The basic idea of model-based clustering is to approximate the data density by a mixture model, typically a mix...
Jeremy Tantrum, Alejandro Murua, Werner Stuetzle
BMCBI
2008
122views more  BMCBI 2008»
13 years 9 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»
13 years 8 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
EACL
2003
ACL Anthology
13 years 10 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
BIOINFORMATICS
2005
70views more  BIOINFORMATICS 2005»
13 years 9 months ago
BioIE: extracting informative sentences from the biomedical literature
e: An interactive visualisation tool for clustering PubMed abstracts METIS: Multiple Extraction Techniques for Informative Sentences BioIE: extracting informative sentences from th...
Anna Divoli, Teresa K. Attwood