Abstract
This article deals with the problem of Cross-Lingual Text Categorization (CLTC), which arises when documents in different languages must be classified according to the same classification tree. We describe practical and cost-effective solutions for automatic Cross-Lingual Text Categorization, both in case a sufficient number of training examples is available for each new language and in the case that for some language no training examples are available.
Experimental results of the bi-lingual classification of the ILO corpus (with documents in English and Spanish) are obtained using bi-lingual training, terminology translation and profile-based translation.
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Bel, N., Koster, C.H.A., Villegas, M. (2003). Cross-Lingual Text Categorization. In: Koch, T., Sølvberg, I.T. (eds) Research and Advanced Technology for Digital Libraries. ECDL 2003. Lecture Notes in Computer Science, vol 2769. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-45175-4_13
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DOI: https://doi.org/10.1007/978-3-540-45175-4_13
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