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EDBT
2008
ACM
167views Database» more  EDBT 2008»
16 years 6 months ago
HISSCLU: a hierarchical density-based method for semi-supervised clustering
In situations where class labels are known for a part of the objects, a cluster analysis respecting this information, i.e. semi-supervised clustering, can give insight into the cl...
Christian Böhm, Claudia Plant
GIS
2002
ACM
15 years 6 months ago
Opening the black box: interactive hierarchical clustering for multivariate spatial patterns
Clustering is one of the most important tasks for geographic knowledge discovery. However, existing clustering methods have two severe drawbacks for this purpose. First, spatial c...
Diansheng Guo, Donna Peuquet, Mark Gahegan
JCB
2002
160views more  JCB 2002»
15 years 6 months ago
Inference from Clustering with Application to Gene-Expression Microarrays
There are many algorithms to cluster sample data points based on nearness or a similarity measure. Often the implication is that points in different clusters come from different u...
Edward R. Dougherty, Junior Barrera, Marcel Brun, ...
BMCBI
2008
259views more  BMCBI 2008»
15 years 6 months ago
DISCLOSE : DISsection of CLusters Obtained by SEries of transcriptome data using functional annotations and putative transcripti
Background: A typical step in the analysis of gene expression data is the determination of clusters of genes that exhibit similar expression patterns. Researchers are confronted w...
Evert-Jan Blom, Sacha A. F. T. van Hijum, Klaas J....
CSMR
2007
IEEE
16 years 23 days ago
The Dynamic Function Coupling Metric and Its Use in Software Evolution
Many of the existing techniques for impact set computation in change propagation and regression testing are approximate for the sake of efficiency. A way to improve precision is ...
Árpád Beszédes, Tamás ...