A massively parallel architecture for a self-organizing neural pattern recognition machine
Computer Vision, Graphics, and Image Processing
Applied multivariate statistical analysis
Applied multivariate statistical analysis
Self-organization and associative memory: 3rd edition
Self-organization and associative memory: 3rd edition
Parallel distributed processing: explorations in the microstructure of cognition, vol. 1: foundations
Neural Networks
An adaptive integrated fuzzy clustering model for pattern recognition
Fuzzy Sets and Systems - Special issue on fuzzy methods for computer vision and pattern recognition
Neuro-fuzzy and soft computing: a computational approach to learning and machine intelligence
Neuro-fuzzy and soft computing: a computational approach to learning and machine intelligence
Improvement of Artificial Odor Discrimination System Using Fuzzy-LVQ Neural Network
ICCIMA '99 Proceedings of the 3rd International Conference on Computational Intelligence and Multimedia Applications
Dimensionality in fuzzy systems
Dimensionality in fuzzy systems
Pattern Classification (2nd Edition)
Pattern Classification (2nd Edition)
A Novel Kernel Method for Clustering
IEEE Transactions on Pattern Analysis and Machine Intelligence
Dynamic Cluster Formation Using Level Set Methods
IEEE Transactions on Pattern Analysis and Machine Intelligence
Evaluation of Stability of k-Means Cluster Ensembles with Respect to Random Initialization
IEEE Transactions on Pattern Analysis and Machine Intelligence
Fuzzy Probability and Statistics (Studies in Fuzziness and Soft Computing)
Fuzzy Probability and Statistics (Studies in Fuzziness and Soft Computing)
The modified fuzzy art and a two-stage clustering approach to cell design
Information Sciences: an International Journal
Clustering algorithm for intuitionistic fuzzy sets
Information Sciences: an International Journal
On the concept of fuzzy probabilistic controllers
Fuzzy Sets and Systems
An integrated approach to fuzzy learning vector quantization and fuzzy c-means clustering
IEEE Transactions on Fuzzy Systems
A Possibilistic Fuzzy c-Means Clustering Algorithm
IEEE Transactions on Fuzzy Systems
IEEE Transactions on Fuzzy Systems
Fuzzy min-max neural networks -- Part 2: Clustering
IEEE Transactions on Fuzzy Systems
A methodology for constructing fuzzy algorithms for learning vector quantization
IEEE Transactions on Neural Networks
Information Sciences: an International Journal
Information Sciences: an International Journal
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A novel fuzzy clustering technique, called iterative Bayesian fuzzy clustering (IBFC), is presented and applied for grouping and recommendation of icons associated with assistive software meant for the physically disabled. The algorithm incorporates a modified fuzzy competitive learning structure with a Bayesian decision rule. In order to ignore unintended behavior of the user, a Bayesian minimum risk classification rule with two loss coefficients is built into the algorithm. This provides a rational basis for outlier detection in noisy data. In addition, we show that the inclusion of a unique control parameter of IBFC allows for establishment of a strong relationship between learning region and cluster congestion. This interpretation leads to an agglomerative iterative Bayesian fuzzy clustering (AIBFC) framework capable of clustering data of complex structure. The proposed AIBFC framework is applied to design a flexible interface for the icon-based assistive software for the disabled. The latter is utilized in grouping and recommendation of icons. Additionally, the proposed algorithm is shown to outperform several well-known methods for both IRIS and Wisconsin benchmark data sets. Finally, it is shown, using a questionnaire survey of real end-users, that the software designed using AIBFC framework meets users' needs.