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Correlation clustering

Clustering is the problem of partitioning data points into groups based on their similarity. Correlation clustering provides a method for clustering… 
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Related topics

Related topics

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Approximation algorithmBiclusteringClustering high-dimensional dataDecorrelation

Broader (1)

Cluster analysis

Papers overview

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2017
2017
Priority Based New Approach for Correlation Clustering
Emerging source of Information like social network, bibliographic data and interaction network of proteins have complex relation… 
Review
2016
Review
2016
Advancement in Clustering with the Concept of Correlation Clustering: A Survey
–Today many scientific, medical and business applications depend heavily on information derived through analysis of large data… 
2015
2015
Hierarchical Planar Correlation Clustering for Cell Segmentation
We introduce a novel algorithm for hierarchical clustering on planar graphs we call “Hierarchical Greedy Planar Correlation… 
2011
2011
Scaling Inference for Markov Logic with a Task-Decomposition Approach
Motivated by applications in large-scale knowledge base construction, we study the problem of scaling up a sophisticated… 
2010
2010
Correlation Clustering Model for Crime Pattern Detection
Detecting crime from data analysis can be difficult because daily activities of criminal generate large amounts of data. The… 
2008
2008
MOLECULAR DYNAMICS APPROACH TO CORRELATION CLUSTERING
A many-body system with co-existing attractive and repulsive interactions is considered on a ring. The competing interactions… 
2007
2007
LINEAR MANIFOLD CORRELATION CLUSTERING
The detection of correlations is a data mining task of increa sing importance due to new areas of application such as DNA… 
2006
2006
EGEA : A New Hybrid Approach Towards Extracting Reduced Generic Association Rule Set (Application to AML Blood Cancer Therapy)
To avoid obtaining an unmanageable highly sized association rule sets– compounded with their low precision– that often make the… 
2005
2005
Clustering of Correlated Documents into Designated Number of Clusters : A Practical Approach
We consider a complete graph to cluster the vertices into k-clusters, where each edge of the graph is labeled either as “+” or… 
2004
2004
Model-based Clustering With Soft And Probabilistic Constraints
The problem of clustering with constraints has received a lot of attention lately. Many existing algorithms assume the specified…