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PKDD
2009
Springer
175views Data Mining» more  PKDD 2009»
15 years 8 months ago
Latent Dirichlet Bayesian Co-Clustering
Co-clustering has emerged as an important technique for mining contingency data matrices. However, almost all existing coclustering algorithms are hard partitioning, assigning each...
Pu Wang, Carlotta Domeniconi, Kathryn B. Laskey
CDC
2008
IEEE
147views Control Systems» more  CDC 2008»
15 years 8 months ago
Clustering neural spike trains with transient responses
— The detection of transient responses, i.e. non– stationarities, that arise in a varying and small fraction of the total number of neural spike trains recorded from chronicall...
John D. Hunter, Jianhong Wu, John G. Milton
KBSE
2008
IEEE
15 years 8 months ago
Using Cluster Analysis to Improve the Design of Component Interfaces
For large software systems, interface structure has an important impact on their maintainability and build performance. For example, for complex systems written in C, recompilatio...
Rahmat Adnan, Bas Graaf, Arie van Deursen, Joost Z...
ICDM
2007
IEEE
129views Data Mining» more  ICDM 2007»
15 years 8 months ago
Semi-supervised Clustering Using Bayesian Regularization
Text clustering is most commonly treated as a fully automated task without user supervision. However, we can improve clustering performance using supervision in the form of pairwi...
Zuobing Xu, Ram Akella, Mike Ching, Renjie Tang
ISBRA
2007
Springer
15 years 8 months ago
Discovering Relations Among GO-Annotated Clusters by Graph Kernel Methods
The biological interpretation of large-scale gene expression data is one of the challenges in current bioinformatics. The state-of-theart approach is to perform clustering and then...
Italo Zoppis, Daniele Merico, Marco Antoniotti, Bu...