InforLorV4, Main, Exploration, bibRecord, 009255

Using artificial neural networks for mapping of scienceand technology: A multi-self-organizing-maps approach

Identifieur interne : 009255 ( Main/Exploration ); précédent : 009254; suivant : 009256

Using artificial neural networks for mapping of scienceand technology: A multi-self-organizing-maps approach

Auteurs : Xavier Polanco [France] ; Claire François [France] ; Jean-Charles Lamirel [France]

Source :

Scientometrics [ 0138-9130 ] ; 2001-04-01.

RBID : ISTEX:611BC9E52B694ADA5748DD91EEF5379215628568

Descripteurs français

Pascal (Inist)
- Amas, Analyse donnée, Analyse exploratoire, Carte électronique, Cartographie information, Génétique, Kohonen (T.), Plante transgénique, Représentation connaissances, Réseau neuronal, Science, Self organizing map, Technologie, Visualisation.
Wicri :
- topic : Génétique, Plante transgénique, Technologie.
mix :
- adaptive model, analyse de l'information, extensions du modèle som, information analizis, modèles adaptatifs, neural networks, réseaux neuronaux, som extensions.

English descriptors

KwdEn :
- Cluster, Data analysis, Exploratory analysis, Genetics, Information mapping, Knowledge representation, Neural network, Printed circuit board, Sciences, Technology, Transgenic plant, Visualization.

Abstract

Abstract: We argue in favour of artificial neural networks for exploratory data analysis, clustering andmapping. We propose the Kohonen self-organizing map (SOM) for clustering and mappingaccording to a multi-maps extension. It is consequently called Multi-SOM. Firstly the KohonenSOM algorithm is presented. Then the following improvements are detailed: the way of namingthe clusters, the map division into logical areas, and the map generalization mechanism. Themulti-map display founded on the inter-maps communication mechanism is exposed, and thenotion of the viewpoint is introduced. The interest of Multi-SOM is presented for visualization,exploration or browsing, and moreover for scientific and technical information analysis. A casestudy in patent analysis on transgenic plants illustrates the use of the Multi-SOM. We also showthat the inter-map communication mechanism provides support for watching the plants on whichpatented genetic technology works. It is the first map. The other four related maps provideinformation about the plant parts that are concerned, the target pathology, the transgenictechniques used for making these plants resistant, and finally the firms involved in geneticengineering and patenting. A method of analysis is also proposed in the use of this computerbasedmulti-maps environment. Finally, we discuss some critical remarks about the proposedapproach at its current state. And we conclude about the advantages that it provides for aknowledge-oriented watching analysis on science and technology. In relation with this remark weintroduce in conclusion the notion of knowledge indicators.

Url:

DOI: 10.1023/A:1010537316758

Affiliations:

Le document en format XML

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<front><div type="abstract" xml:lang="en">Abstract: We argue in favour of artificial neural networks for exploratory data analysis, clustering andmapping. We propose the Kohonen self-organizing map (SOM) for clustering and mappingaccording to a multi-maps extension. It is consequently called Multi-SOM. Firstly the KohonenSOM algorithm is presented. Then the following improvements are detailed: the way of namingthe clusters, the map division into logical areas, and the map generalization mechanism. Themulti-map display founded on the inter-maps communication mechanism is exposed, and thenotion of the viewpoint is introduced. The interest of Multi-SOM is presented for visualization,exploration or browsing, and moreover for scientific and technical information analysis. A casestudy in patent analysis on transgenic plants illustrates the use of the Multi-SOM. We also showthat the inter-map communication mechanism provides support for watching the plants on whichpatented genetic technology works. It is the first map. The other four related maps provideinformation about the plant parts that are concerned, the target pathology, the transgenictechniques used for making these plants resistant, and finally the firms involved in geneticengineering and patenting. A method of analysis is also proposed in the use of this computerbasedmulti-maps environment. Finally, we discuss some critical remarks about the proposedapproach at its current state. And we conclude about the advantages that it provides for aknowledge-oriented watching analysis on science and technology. In relation with this remark weintroduce in conclusion the notion of knowledge indicators.</div>
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Using artificial neural networks for mapping of scienceand technology: A multi-self-organizing-maps approach

Using artificial neural networks for mapping of scienceand technology: A multi-self-organizing-maps approach

Source :

Descripteurs français

English descriptors

Abstract

Links toward previous steps (curation, corpus...)

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