Adaptive Dictionary for Bilingual Lexicon Extraction from Comparable Corpora

13545

Authors

nan

Abstract

AbstractOne of the main resources used for the task of bilingual lexicon extraction from comparable corpora is : the bilingual dictionary, which is considered as a bridge between two languages. However, no particular attention has been given to this lexicon, except its coverage, and the fact that it can be issued from the general language, the specialised one, or a mix of both. In this paper, we want to highlight the idea that a better consideration of the bilingual dictionary by studying its entries and filtering the non-useful ones, leads to a better lexicon extraction and thus, reach a higher precision. The experiments are conducted on a medical domain corpora. The French-English specialised corpus 'breast cancer' of 1 million words. We show that the empirical results obtained with our filtering process improve the standard approach traditionally dedicated to this task and are promising for future work.

Keywords

nan

Full Content

nan

Labeled Text

AbstractOne of the main resources used for the task of bilingual lexicon extraction from comparable corpora is : the bilingual dictionary, which is considered as a bridge between two languages. However, no particular attention has been given to this lexicon, except its coverage, and the fact that it can be issued from the general language, the specialised one, or a mix of both. In this paper, we want to highlight the idea that a better consideration of the bilingual dictionary by studying its entries and filtering the non-useful ones, leads to a better lexicon extraction and thus, reach a higher precision. The experiments are conducted on a medical domain corpora. The French-English specialised corpus 'breast cancer' of 1 million words. We show that the empirical results obtained with our filtering process improve the standard approach traditionally dedicated to this task and are promising for future work.

Publication Details

Paper ID:
13545
Year:
2012
Publication:
TIPSTER
Publication Type:
conf
DOI:
nan