Artificial Neural Network Technology: for Classification and Cartography of Scientific and Technical Information

Abstract

This paper describes the implementation of multivariate data analysis: NEURODOC applies the axial k-means method for automatic, non-hierarchical cluster analysis and a Principal Component Analysis (PCA) for representing the clusters on a map. We next introduce Artificial Neural Networks (ANNs) to extend NEURODOC into a neural platform for the cluster analysis and cartography of bibliographic data. The ANNs tested are: the Adaptive Resonance Theory (ART 1), a Multilayer Perceptron (MLP), and an associative network with unsupervised learning (KOHONEN). This platform is intended for quantitative analysis of information.

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Cite this paper

@inproceedings{Polanco2008ArtificialNN, title={Artificial Neural Network Technology: for Classification and Cartography of Scientific and Technical Information}, author={Xavier Polanco}, year={2008} }