Skip to search formSkip to main contentSkip to account menu

Correlation clustering

Clustering is the problem of partitioning data points into groups based on their similarity. Correlation clustering provides a method for clustering… 
Wikipedia (opens in a new tab)

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
2015
2015
We introduce a novel algorithm for hierarchical clustering on planar graphs we call “Hierarchical Greedy Planar Correlation… 
2013
2013
We introduce a method to discover objects from RGB-D image collections which does not require a user to specify the number of… 
2011
2011
Motivated by applications in large-scale knowledge base construction, we study the problem of scaling up a sophisticated… 
2010
2010
After optimizing filter back projection (FBP) algorithm of CT with the theory of symmetric transformation group and based on the… 
2009
2009
Random networks with co-existing positive and negative links are studied from the viewpoint of the NP hard correlation clustering… 
2009
2009
This thesis investigates application of clustering to multi-criteria ratings as a method of improving the precision of top-N… 
2009
2009
The Consensus Clustering problem has been introduced as an effective way to analyze the results of different microarray… 
2007
2007
The detection of correlations is a data mining task of increa sing importance due to new areas of application such as DNA… 
2005
2005
In this paper we describe a new cluster model which is based on the concept of linear manifolds. The method identifies subsets of… 
2004
2004
The problem of clustering with constraints has received a lot of attention lately. Many existing algorithms assume the specified…