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» Clustering by pattern similarity in large data sets
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SOCIALCOM
2010
13 years 5 months ago
Measuring Similarity between Sets of Overlapping Clusters
The typical task of unsupervised learning is to organize data, for example into clusters, typically disjoint clusters (eg. the K-means algorithm). One would expect (for example) a...
Mark K. Goldberg, Mykola Hayvanovych, Malik Magdon...
CIDM
2007
IEEE
14 years 1 months ago
Mining Subspace Correlations
— In recent applications of clustering such as gene expression microarray analysis, collaborative filtering, and web mining, object similarity is no longer measured by physical ...
Rave Harpaz, Robert M. Haralick
SIGMOD
1998
ACM
99views Database» more  SIGMOD 1998»
13 years 11 months ago
CURE: An Efficient Clustering Algorithm for Large Databases
Clustering, in data mining, is useful for discovering groups and identifying interesting distributions in the underlying data. Traditional clustering algorithms either favor clust...
Sudipto Guha, Rajeev Rastogi, Kyuseok Shim
BMCBI
2007
133views more  BMCBI 2007»
13 years 7 months ago
Semi-supervised learning for the identification of syn-expressed genes from fused microarray and in situ image data
Background: Gene expression measurements during the development of the fly Drosophila melanogaster are routinely used to find functional modules of temporally co-expressed genes. ...
Ivan G. Costa, Roland Krause, Lennart Opitz, Alexa...
IDA
2006
Springer
13 years 7 months ago
Supporting bi-cluster interpretation in 0/1 data by means of local patterns
Clustering or co-clustering techniques have been proved useful in many application domains. A weakness of these techniques remains the poor support for grouping characterization. ...
Ruggero G. Pensa, Céline Robardet, Jean-Fra...