Fuzzy mathematical techniques with applications
Fuzzy mathematical techniques with applications
Characterization and detection of noise in clustering
Pattern Recognition Letters
Communications of the ACM
Fuzzy logic controller design utilizing multiple contending software agents
Fuzzy Sets and Systems
A soft computing framework for adaptive agents
Soft computing agents
Pattern Recognition with Fuzzy Objective Function Algorithms
Pattern Recognition with Fuzzy Objective Function Algorithms
Fuzzy Sets Engineering
Pattern Classification (2nd Edition)
Pattern Classification (2nd Edition)
A fuzzy clustering-based rapid prototyping for fuzzy rule-based modeling
IEEE Transactions on Fuzzy Systems
Fuzzy order statistics and their application to fuzzy clustering
IEEE Transactions on Fuzzy Systems
Supervised fuzzy clustering for rule extraction
IEEE Transactions on Fuzzy Systems
Conditional fuzzy clustering in the design of radial basis function neural networks
IEEE Transactions on Neural Networks
Robust centroids using fuzzy clustering with feature partitions
Pattern Recognition Letters
Fuzzy clustering in parallel universes
International Journal of Approximate Reasoning
A consensus-driven fuzzy clustering
Pattern Recognition Letters
Collaborative clustering with the use of Fuzzy C-Means and its quantification
Fuzzy Sets and Systems
Robust fuzzy clustering using mixtures of Student's-t distributions
Pattern Recognition Letters
CONSENSUS-BASED ENSEMBLES OF SOFT CLUSTERINGS
Applied Artificial Intelligence
Interpretability constraints for fuzzy information granulation
Information Sciences: an International Journal
Metastructural facets of granular computing
International Journal of Knowledge Engineering and Soft Data Paradigms
A multifaceted perspective at data analysis: a study in collaborative intelligent agents
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics - Special issue on cybernetics and cognitive informatics
Collaborative clustering with background knowledge
Data & Knowledge Engineering
The model of generalized partially horizontal collaborative fuzzy C-means
CCDC'09 Proceedings of the 21st annual international conference on Chinese control and decision conference
A novel hierarchical-clustering-combination scheme based on fuzzy-similarity relations
IEEE Transactions on Fuzzy Systems
Application of rough sets in pattern recognition
Transactions on rough sets VII
Learning collaboration links in a collaborative fuzzy clustering environment
MICAI'07 Proceedings of the artificial intelligence 6th Mexican international conference on Advances in artificial intelligence
Collaborative architectures of fuzzy modeling
WCCI'08 Proceedings of the 2008 IEEE world conference on Computational intelligence: research frontiers
The structural clustering and analysis of metric based on granular space
Pattern Recognition
PSO driven collaborative clustering: A clustering algorithm for ubiquitous environments
Intelligent Data Analysis - Ubiquitous Knowledge Discovery
New results on a fuzzy granular space
ICSI'11 Proceedings of the Second international conference on Advances in swarm intelligence - Volume Part I
Partitioning hard clustering algorithms based on multiple dissimilarity matrices
Pattern Recognition
Collaborative rough clustering
PReMI'05 Proceedings of the First international conference on Pattern Recognition and Machine Intelligence
Adjusting the clustering results referencing an external set
ICSI'10 Proceedings of the First international conference on Advances in Swarm Intelligence - Volume Part II
Collaborative generative topographic mapping
ICONIP'12 Proceedings of the 19th international conference on Neural Information Processing - Volume Part II
Relational partitioning fuzzy clustering algorithms based on multiple dissimilarity matrices
Fuzzy Sets and Systems
Soft clustering -- Fuzzy and rough approaches and their extensions and derivatives
International Journal of Approximate Reasoning
A Fast Multiclass Classification Algorithm Based on Cooperative Clustering
Neural Processing Letters
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In this study, we introduce a new clustering architecture in which several subsets of patterns can be processed together with an objective of finding a structure that is common to all of them. To reveal this structure, the clustering algorithms operating on the separate subsets of data collaborate by exchanging information about local partition matrices. In this sense, the required communication links are established at the level of information granules (more specifically, fuzzy sets forming the partition matrices) rather than patterns that are directly available in the databases. We discuss how this form of collaboration helps meet requirements of data confidentiality. A detailed clustering algorithm is developed on a basis of the standard FCM method and illustrated by means of numeric examples.