Abstract
This paper is positioned within the development of an automated indexing system for the CISMeF quality controlled health gateway. For disambiguation purposes, we wish to perform text categorization prior to indexing. Hence, a global approach contrasting with the classical analytical methods based on the analysis of keyword counts extracted from the text is necessary. The use of statistical compression models enables us to proceed avoiding keyword extraction at this stage. Preliminary results show that althought this method is not as precise as others in terms of resource categorization, it can significantly benefit indexing.
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Rogozan, A., Néveol, A., Darmoni, S.J. (2003). Text Categorization prior to Indexing for the CISMEF Health Catalogue. In: Dojat, M., Keravnou, E.T., Barahona, P. (eds) Artificial Intelligence in Medicine. AIME 2003. Lecture Notes in Computer Science(), vol 2780. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-39907-0_12
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DOI: https://doi.org/10.1007/978-3-540-39907-0_12
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