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» Cluster analysis of heterogeneous rank data
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PRL
2010
158views more  PRL 2010»
14 years 8 months ago
Data clustering: 50 years beyond K-means
: Organizing data into sensible groupings is one of the most fundamental modes of understanding and learning. As an example, a common scheme of scientific classification puts organ...
Anil K. Jain
SIGIR
2004
ACM
15 years 3 months ago
Learning to cluster web search results
Organizing Web search results into clusters facilitates users' quick browsing through search results. Traditional clustering techniques are inadequate since they don't g...
Hua-Jun Zeng, Qi-Cai He, Zheng Chen, Wei-Ying Ma, ...
IBPRIA
2007
Springer
15 years 3 months ago
Motion Segmentation from Feature Trajectories with Missing Data
Abstract. This paper presents a novel approach for motion segmentation from feature trajectories with missing data. It consists of two stages. In the first stage, missing data are...
Carme Julià, Angel Domingo Sappa, Felipe Lu...
BMCBI
2010
164views more  BMCBI 2010»
14 years 7 months ago
Merged consensus clustering to assess and improve class discovery with microarray data
Background: One of the most commonly performed tasks when analysing high throughput gene expression data is to use clustering methods to classify the data into groups. There are a...
T. Ian Simpson, J. Douglas Armstrong, Andrew P. Ja...
BIBM
2007
IEEE
137views Bioinformatics» more  BIBM 2007»
15 years 4 months ago
A Multi-metric Similarity Based Analysis of Microarray Data
Clustering has been shown to be effective in analyzing functional relationships of genes. However, no single clustering method with single distance metric is capable of capturing ...
Fatih Altiparmak, Selnur Erdal, Ozgur Ozturk, Haka...