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TKDE
2008
127views more  TKDE 2008»
13 years 7 months ago
Maximal Subspace Coregulated Gene Clustering
Clustering is a popular technique for analyzing microarray data sets, with n genes and m experimental conditions. As explored by biologists, there is a real need to identify coregu...
Yuhai Zhao, Jeffrey Xu Yu, Guoren Wang, Lei Chen 0...
ISPASS
2006
IEEE
14 years 1 months ago
Comparing multinomial and k-means clustering for SimPoint
SimPoint is a technique used to pick what parts of the program’s execution to simulate in order to have a complete picture of execution. SimPoint uses data clustering algorithms...
Greg Hamerly, Erez Perelman, Brad Calder
SIGIR
2000
ACM
14 years 2 days ago
An investigation of linguistic features and clustering algorithms for topical document clustering
We investigate four hierarchical clustering methods (single-link, complete-link, groupwise-average, and single-pass) and two linguistically motivated text features (noun phrase he...
Vasileios Hatzivassiloglou, Luis Gravano, Ankineed...
KDD
2003
ACM
129views Data Mining» more  KDD 2003»
14 years 8 months ago
Nantonac collaborative filtering: recommendation based on order responses
A recommender system suggests the items expected to be preferred by the users. Recommender systems use collaborative filtering to recommend items by summarizing the preferences of...
Toshihiro Kamishima
HAIS
2008
Springer
13 years 8 months ago
Clustering Likelihood Curves: Finding Deviations from Single Clusters
For systematic analyses of quantitative mass spectrometry data a method was developed in order to reveal peptides within a protein, that show differences in comparison with the rem...
Claudia Hundertmark, Frank Klawonn