Self-Organizing Maps
Neural Network Based Document Clustering Using WordNet Ontologies
International Journal of Hybrid Intelligent Systems
Self organization of a massive document collection
IEEE Transactions on Neural Networks
Learning a taxonomy from a set of text documents
Applied Soft Computing
Matching semi-structured documents using similarity of regions through fuzzy rule-based system
ICDM'13 Proceedings of the 13th international conference on Advances in Data Mining: applications and theoretical aspects
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This article introduces and evaluates a fuzzy logic based representation for HTML document clustering using Self-Organizing Maps. This representation is built on heuristic combinations of criteria by means of a fuzzy rules system and based on the HTML markup. We evaluate the model using different feature vector sizes. Experimental results show an improvement in clustering quality when the fuzzy logic-based model is used instead of the vector space model with traditional term weighting functions in a standard benchmark dataset.