Abstract
This paper aims at exploring the capability of the so called Latent Semantic Analysis applied to a multilingual context. In particular we are interested in weighing how it could be useful in solving linguistic problems, moving from a statistical point of view. Here we focus on the possibility of evaluating the goodness of a translation by comparing the latent structures of the original text and its version in another natural language. Procrustes rotations are introduced in a statistical framework as a tool for reaching this goal. An application on one year of Le Monde Diplomatique and the corresponding Italian edition will show the effectiveness of our proposal.
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Balbi, S., Misuraca, M. (2006). Procrustes Techniques for Text Mining. In: Zani, S., Cerioli, A., Riani, M., Vichi, M. (eds) Data Analysis, Classification and the Forward Search. Studies in Classification, Data Analysis, and Knowledge Organization. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-35978-8_26
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DOI: https://doi.org/10.1007/3-540-35978-8_26
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