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Consensus clustering

Clustering is the assignment of objects into groups (called clusters) so that objects from the same cluster are more similar to each other than… 
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Related topics

Related topics

13 relations
Binarization of consensus partition matricesBioinformaticsData miningEnsemble learning

Broader (1)

Cluster analysis

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
Highly Cited
2019
Highly Cited
2019
Ultra-Scalable Spectral Clustering and Ensemble Clustering
This paper focuses on scalability and robustness of spectral clustering for extremely large-scale datasets with limited resources… 
Review
2018
Review
2018
Security Threats Classification in Blockchains
Blockchain, the foundation of Bitcoin, has become one of the most popular technologies to create and manage digital transactions… 
2017
2017
Mining Community Structures in Multidimensional Networks
We investigate the problem of community detection in multidimensional networks, that is, networks where entities engage in… 
Highly Cited
2015
Highly Cited
2015
K-Means-Based Consensus Clustering: A Unified View
The objective of consensus clustering is to find a single partitioning which agrees as much as possible with existing basic… 
Highly Cited
2014
Highly Cited
2014
Combining multiple clusterings via crowd agreement estimation and multi-granularity link analysis
Highly Cited
2012
Highly Cited
2012
Cluster ensembles in collaborative filtering recommendation
Highly Cited
2011
Highly Cited
2011
Distributed Higher Order Consensus Protocols in Multiagent Dynamical Systems
This paper studies general higher order distributed consensus protocols in multiagent dynamical systems. First, network… 
Highly Cited
2008
Highly Cited
2008
Weighted Consensus Clustering
Consensus clustering has emerged as an important extension of the classical clustering problem. We propose weighted consensus… 
Highly Cited
2008
Highly Cited
2008
Consensus Clustering Algorithms: Comparison and Refinement
Consensus clustering is the problem of reconciling clustering information about the same data set coming from different sources… 
Highly Cited
2006
Highly Cited
2006
Moderate diversity for better cluster ensembles
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