Towards a robust fuzzy clustering
Fuzzy Sets and Systems - Data analysis
Fuzzy clustering with a knowledge-based guidance
Pattern Recognition Letters
General C-Means Clustering Model
IEEE Transactions on Pattern Analysis and Machine Intelligence
Data Clustering with Partial Supervision
Data Mining and Knowledge Discovery
Non-Euclidean c-means clustering algorithms
Intelligent Data Analysis
Robust fuzzy relational classifier incorporating the soft class labels
Pattern Recognition Letters
Vagueness and uncertainty in information retrieval: how can fuzzy sets help?
Proceedings of the 2006 international workshop on Research issues in digital libraries
Analytical and Numerical Evaluation of the Suppressed Fuzzy C-Means Algorithm
MDAI '08 Sabadell Proceedings of the 5th International Conference on Modeling Decisions for Artificial Intelligence
On the efficiency of evolutionary fuzzy clustering
Journal of Heuristics
A simultaneous learning framework for clustering and classification
Pattern Recognition
Classification of audio signals using Fuzzy c-Means with divergence-based Kernel
Pattern Recognition Letters
Fuzzy C-Means Cluster Segmentation Algorithm Based on Modified Membership
ISNN 2009 Proceedings of the 6th International Symposium on Neural Networks: Advances in Neural Networks - Part II
Multi-documents Automatic Abstracting based on text clustering and semantic analysis
Knowledge-Based Systems
Hierarchical-Hyperspherical Divisive Fuzzy C-Means (H2D-FCM) Clustering for Information Retrieval
WI-IAT '09 Proceedings of the 2009 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology - Volume 01
Clustering: A neural network approach
Neural Networks
A time-domain-constrained fuzzy clustering method and its application to signal analysis
Fuzzy Sets and Systems
Enhanced neural gas network for prototype-based clustering
Pattern Recognition
Efficient feature extraction for fast segmentation of MR brain images
SCIA'07 Proceedings of the 15th Scandinavian conference on Image analysis
Collaborative optimization of clustering by fuzzy c-means and weight determination by ReliefF
FSKD'09 Proceedings of the 6th international conference on Fuzzy systems and knowledge discovery - Volume 1
A robust fuzzy local information C-means clustering algorithm
IEEE Transactions on Image Processing
A generalized approach to the suppressed fuzzy c-means algorithm
MDAI'10 Proceedings of the 7th international conference on Modeling decisions for artificial intelligence
A hardware architecture for subtractive clustering
International Journal of High Performance Systems Architecture
Granular representation of temporal signals using differential quadratures
ACIIDS'11 Proceedings of the Third international conference on Intelligent information and database systems - Volume Part II
Hybrid fuzzy clustering using LP norms
ACIIDS'11 Proceedings of the Third international conference on Intelligent information and database systems - Volume Part I
UAHCI'11 Proceedings of the 6th international conference on Universal access in human-computer interaction: applications and services - Volume Part IV
Partitioning hard clustering algorithms based on multiple dissimilarity matrices
Pattern Recognition
Robust data clustering by learning multi-metric Lq-norm distances
Expert Systems with Applications: An International Journal
Reconfigurable hardware to radionuclide identification using subtractive clustering
ICA3PP'11 Proceedings of the 11th international conference on Algorithms and architectures for parallel processing - Volume Part II
Alternative fuzzy clustering algorithms with l1-norm and covariance matrix
ACIVS'06 Proceedings of the 8th international conference on Advanced Concepts For Intelligent Vision Systems
A novel clustering method for analysis of gene microarray expression data
BioDM'06 Proceedings of the 2006 international conference on Data Mining for Biomedical Applications
An alternative fuzzy compactness and separation clustering algorithm
ACIVS'05 Proceedings of the 7th international conference on Advanced Concepts for Intelligent Vision Systems
A quality driven Hierarchical Data Divisive Soft Clustering for information retrieval
Knowledge-Based Systems
Fuzzy and possibilistic clustering for fuzzy data
Computational Statistics & Data Analysis
An improved clustering algorithm for information granulation
FSKD'05 Proceedings of the Second international conference on Fuzzy Systems and Knowledge Discovery - Volume Part I
A flexible news filtering model exploiting a hierarchical fuzzy categorization
FQAS'06 Proceedings of the 7th international conference on Flexible Query Answering Systems
Impulsive noise cancelation with simplified Cauchy-based p-norm filter
Signal Processing
Hierarchical clustering in power system based on fuzzy transitive closure
WSEAS Transactions on Circuits and Systems
Segmentation of images with separating layers by fuzzy c-means and convex optimization
Journal of Visual Communication and Image Representation
Partitive clustering (K-means family)
Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery
A modified fuzzy C-means algorithm for MR brain image segmentation
ICIAR'07 Proceedings of the 4th international conference on Image Analysis and Recognition
Effective FCM noise clustering algorithms in medical images
Computers in Biology and Medicine
A multivariate fuzzy c-means method
Applied Soft Computing
On possibilistic clustering with repulsion constraints for imprecise data
Information Sciences: an International Journal
Hardware implementation of subtractive clustering for radionuclide identification
Integration, the VLSI Journal
A size-insensitive integrity-based fuzzy c-means method for data clustering
Pattern Recognition
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Fuzzy c-means (FCM) is a useful clustering technique. Modifications of FCM using L1 norm distances increase robustness to outliers. Object and relational data versions of FCM clustering are defined for the more general case where the Lp norm (p⩾1) or semi-norm (0
0 in order to facilitate the empirical examination of the object data models. Both object and relational approaches are included in a numerical study