IEEE Transactions on Pattern Analysis and Machine Intelligence
Word sense disambiguation for free-text indexing using a massive semantic network
CIKM '93 Proceedings of the second international conference on Information and knowledge management
Interpreting the Kohonen self-organizing feature map using contiguity-constrained clustering
Pattern Recognition Letters
Extending the Kohonen self-organizing map networks for clustering analysis
Computational Statistics & Data Analysis
C4.5: Programs for Machine Learning
C4.5: Programs for Machine Learning
How to make large self-organizing maps for nonvectorial data
Neural Networks - New developments in self-organizing maps
Data visualisation and manifold mapping using the ViSOM
Neural Networks - New developments in self-organizing maps
Adaptive double self-organizing maps for clustering gene expression profiles
Neural Networks - 2003 Special issue: Advances in neural networks research — IJCNN'03
SOM-based algorithms for qualitative variables
Neural Networks - 2004 Special issue: New developments in self-organizing systems
Neural Networks - 2006 Special issue: Advances in self-organizing maps--WSOM'05
On the equivalence between kernel self-organising maps and self-organising mixture density networks
Neural Networks - 2006 Special issue: Advances in self-organizing maps--WSOM'05
Hierarchical clustering of mixed data based on distance hierarchy
Information Sciences: an International Journal
A Nonlinear Mapping for Data Structure Analysis
IEEE Transactions on Computers
A Multi-criteria Convex Quadratic Programming model for credit data analysis
Decision Support Systems
Incremental clustering of mixed data based on distance hierarchy
Expert Systems with Applications: An International Journal
On clustering tree structured data with categorical nature
Pattern Recognition
Exploring Topology Preservation of SOMs with a Graph Based Visualization
IDEAL '08 Proceedings of the 9th International Conference on Intelligent Data Engineering and Automated Learning
Probabilistic Mixed Topological Map for Categorical and Continuous Data
ICMLA '08 Proceedings of the 2008 Seventh International Conference on Machine Learning and Applications
Using information content to evaluate semantic similarity in a taxonomy
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 1
Exploiting data topology in visualization and clustering of self-organizing maps
IEEE Transactions on Neural Networks
Visualising class distribution on self-organising maps
ICANN'07 Proceedings of the 17th international conference on Artificial neural networks
Topographic mapping of large dissimilarity data sets
Neural Computation
Advanced visualization techniques for self-organizing maps with graph-based methods
ISNN'05 Proceedings of the Second international conference on Advances in neural networks - Volume Part II
An extension of self-organizing maps to categorical data
EPIA'05 Proceedings of the 12th Portuguese conference on Progress in Artificial Intelligence
Clustering of the self-organizing map
IEEE Transactions on Neural Networks
Generalizing self-organizing map for categorical data
IEEE Transactions on Neural Networks
Self-organizing map for symbolic data
Fuzzy Sets and Systems
| Hi-index | 0.01 |
Mixed numeric and categorical data are commonly seen nowadays in corporate databases in which precious patterns may be hidden. Analyzing mixed-type data to extract the hidden patterns valuable to decision-making is therefore beneficial and critical for corporations to remain competitive. In addition, visualization facilitates exploration in the early stage of data analysis. In the paper, we present a visualized approach to analyzing multivariate mixed-type data. The proposed framework based on an extended self-organizing map allows visualized data cluster analysis as well as classification. We demonstrate the feasibility of the approach by analyzing two real-world datasets and compare with other existing models to show its advantages.