Neural Networks and Information Extraction: New developments in astronomical information retrieval for electronic publications

Astronomy and Astrophysics – Astronomy

Scientific paper

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Scientific paper

The inlet of electronic publication in astronomy offers a wealth of new possibilities for retrieving and accessing astronomical information. We describe results obtained in prototyping a Kohonen selforganising feature (a neural network approach) as an interface to a large document collection. This tool permits to display density maps and clustering tendencies of the document collection using, in a first step, the keywords of the articles. The resulting clickable map provides direct access to the abstract services. In a second part, we discuss new possibilities for increasing links between electronic texts and astronomical services. The first application is an automatic tagging of object names in an electronic text, in order to link that object name with the SIMBAD data available for the object.

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