By John S. White
Complaints of the 4th convention at the organization for desktop Translation within the Americas, AMTA 2000, held in Cuernavaca, Mexico, October 10-14, 2000. comprises technical papers and process descriptions of computer translation environments. Softcover.
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Additional info for Envisioning Machine Translation in the Information Future: 4th Conference of the Association for Machine Translation in the Americas, AMTA 2000, ...
Define the texts’ beginnings – the point (0,0) – and ends – the point (length of text A, length of text B) – as the extremes of the initial parallel text segment; 36 A. Ribeiro, G. Lopes, and J. Mexia 3. Consider as candidate correspondence points those defined both by homograph and equivalent words (if an extracted bilingual word lexicon is already available) which occur with the same frequency within the parallel text segment; 4. Filter out extreme points using the Histogram technique; 5. Filter out points which lie outside the confidence bands of the regression line; 6.
Information Processing & Management. 28(4) (1992) 491–502 24 A. Fujii and T. Ishikawa 10. Kwok, K. L. : Improving two-stage ad-hoc retrieval for short queries. In Proceedings of the 21st Annual International ACM SIGIR Conference on Research and Development in Information Retrieval. (1998) 250–256 11. , Dumais, S. : Automatic cross-language information retrieval using latent semantic indexing. In Gregory Grefenstette, editor, CrossLanguage Information Retrieval. Kluwer Academic Publishers. (1998) 51–62 12.
Each pair of texts gives a set of candidate correspondence points from which we draw a line based on linear regression. Points are defined using the co-ordinates of the word positions in each parallel text. For example, if the first occurrence of the homograph word México occurs at word position 60311 in the Portuguese text and at 61940 in the Spanish parallel text, then the point co-ordinates are (60311,61940). Points may adjust themselves well to the linear regression line or may be dispersed around it.