Neural networks and fuzzy systems: a dynamical systems approach to machine intelligence
Neural networks and fuzzy systems: a dynamical systems approach to machine intelligence
Self-organization as an iterative kernel smoothing process
Neural Computation
Self-organizing maps
A unifying objective function for topographic mappings
Neural Computation
Journal of the American Society for Information Science - Special issue on science and technology indicators
Journal of the American Society for Information Science
A corpus-based approach to comparative evaluation of statistical term association measures
Journal of the American Society for Information Science and Technology
Modern Information Retrieval
Multivariate Descriptive Statistical Analysis
Multivariate Descriptive Statistical Analysis
Redefining Clustering for High-Dimensional Applications
IEEE Transactions on Knowledge and Data Engineering
A Comparative Study on Feature Selection in Text Categorization
ICML '97 Proceedings of the Fourteenth International Conference on Machine Learning
A Nonlinear Mapping for Data Structure Analysis
IEEE Transactions on Computers
Support vector machine classifiers for asymmetric proximities
ICANN/ICONIP'03 Proceedings of the 2003 joint international conference on Artificial neural networks and neural information processing
Two efficient connectionist schemes for structure preserving dimensionality reduction
IEEE Transactions on Neural Networks
Self organization of a massive document collection
IEEE Transactions on Neural Networks
Interactive visualization and analysis of hierarchical neural projections for data mining
IEEE Transactions on Neural Networks
Self-organizing maps, vector quantization, and mixture modeling
IEEE Transactions on Neural Networks
Combining SVM classifiers for email anti-spam filtering
IWANN'07 Proceedings of the 9th international work conference on Artificial neural networks
An experimental study on asymmetric self-organizing map
IDEAL'11 Proceedings of the 12th international conference on Intelligent data engineering and automated learning
Extending the SOM algorithm to visualize word relationships
IDA'05 Proceedings of the 6th international conference on Advances in Intelligent Data Analysis
k-Means clustering of asymmetric data
HAIS'12 Proceedings of the 7th international conference on Hybrid Artificial Intelligent Systems - Volume Part I
Functional analysis techniques to improve similarity matrices in discrimination problems
Journal of Multivariate Analysis
Data visualization for asymmetric relations
Neurocomputing
Asymmetric clustering using the alpha-beta divergence
Pattern Recognition
| Hi-index | 0.01 |
Multidimensional scaling (MDS) and self organizing maps (SOM) algorithms are useful to visualize object relationships in a data set. These algorithms rely on the use of symmetric distances or similarity measures; for instance the Euclidean distance. There are a number of relevant applications, such as text mining and DNA microarray processing for which it is worth considering non symmetric similarity measures, that allow us to properly represent hierarchical relationships. In this paper we present asymmetric versions of SOM and MDS algorithms able to deal with asymmetric proximity matrices. We also compare these approaches to the corresponding symmetric versions. Experimental work on text databases and gene expression data sets show that the asymmetric proposed algorithms outperform their symmetric counterparts.