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» Classes and clusters in data analysis
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196
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BMCBI
2007
166views more  BMCBI 2007»
15 years 6 months ago
How to decide which are the most pertinent overly-represented features during gene set enrichment analysis
Background: The search for enriched features has become widely used to characterize a set of genes or proteins. A key aspect of this technique is its ability to identify correlati...
Roland Barriot, David J. Sherman, Isabelle Dutour
183
Voted
ACSW
2004
15 years 8 months ago
Visualisation and Comparison of Image Collections based on Self-organised Maps
Self-organised maps (SOM) have been widely used for cluster analysis and visualisation purposes in exploratory data mining. In image retrieval applications, SOMs have been used to...
Da Deng, Jianhua Zhang, Martin K. Purvis
WWW
2008
ACM
16 years 7 months ago
Social and semantics analysis via non-negative matrix factorization
Social media such as Web forum often have dense interactions between user and content where network models are often appropriate for analysis. Joint non-negative matrix factorizat...
Zhi-Li Wu, Chi-Wa Cheng, Chun-hung Li
ICDE
2007
IEEE
165views Database» more  ICDE 2007»
16 years 8 months ago
On Randomization, Public Information and the Curse of Dimensionality
A key method for privacy preserving data mining is that of randomization. Unlike k-anonymity, this technique does not include public information in the underlying assumptions. In ...
Charu C. Aggarwal
CVPR
2005
IEEE
16 years 8 months ago
Subspace Analysis Using Random Mixture Models
In [1], three popular subspace face recognition methods, PCA, Bayes, and LDA were analyzed under the same framework and an unified subspace analysis was proposed. However, since t...
Xiaogang Wang, Xiaoou Tang