Add to ORKGNational audienceCo-clustering aims to identify block patterns in a data table, from a joint clustering of rows and columns. This problem has been studied since 1965, with recent interests in various fields, ranging from graph analysis, machine learning, data mining and genomics. Several variants have been proposed with diverse names: bi-clustering, block clustering, cross-clustering, or simultaneous clustering. We propose here a review of these methods in order to describe, compare and discuss the different possibilities to realize a co-clustering following the user aim
International audienceCo-clustering aims at computing a bi-partition that is a collection of co-clus...
Co-clustering is a specific type of clustering that addresses the problem of simultaneously clusteri...
Although most of the clustering literature focuses on one-sided clustering algorithms, simultaneous ...
Co-clustering aims to identify block patterns in a data table, from a joint clustering of rows and c...
National audienceCo-clustering aims to identify block patterns in a data table, from a joint cluster...
Abstract: One of the major problems in clustering is the need of specifying the optimal number of cl...
International audienceMany of the datasets encountered in statistics are two-dimensional in nature a...
International audienceCo-clustering is a data mining technique used to extract the underlying block ...
Simultaneous clustering of rows and columns, usually designated by bi-clustering, co-clustering or b...
Simultaneous clustering of rows and columns, usually designated by bi-clustering, coclustering or bl...
International audienceCo-clustering is a class of unsupervised data analysis techniques that extract...
Clustering plays an important role in data mining, as it is used by many applications as a preproces...
Cluster or co-cluster analyses are important tools in a variety of scientific areas. The introductio...
International audienceCo-clustering is a data mining technique used to extract the underlying block ...
Co-clustering (also known as biclustering), is an important extension of cluster analysis since it a...
International audienceCo-clustering aims at computing a bi-partition that is a collection of co-clus...
Co-clustering is a specific type of clustering that addresses the problem of simultaneously clusteri...
Although most of the clustering literature focuses on one-sided clustering algorithms, simultaneous ...
Co-clustering aims to identify block patterns in a data table, from a joint clustering of rows and c...
National audienceCo-clustering aims to identify block patterns in a data table, from a joint cluster...
Abstract: One of the major problems in clustering is the need of specifying the optimal number of cl...
International audienceMany of the datasets encountered in statistics are two-dimensional in nature a...
International audienceCo-clustering is a data mining technique used to extract the underlying block ...
Simultaneous clustering of rows and columns, usually designated by bi-clustering, co-clustering or b...
Simultaneous clustering of rows and columns, usually designated by bi-clustering, coclustering or bl...
International audienceCo-clustering is a class of unsupervised data analysis techniques that extract...
Clustering plays an important role in data mining, as it is used by many applications as a preproces...
Cluster or co-cluster analyses are important tools in a variety of scientific areas. The introductio...
International audienceCo-clustering is a data mining technique used to extract the underlying block ...
Co-clustering (also known as biclustering), is an important extension of cluster analysis since it a...
International audienceCo-clustering aims at computing a bi-partition that is a collection of co-clus...
Co-clustering is a specific type of clustering that addresses the problem of simultaneously clusteri...
Although most of the clustering literature focuses on one-sided clustering algorithms, simultaneous ...