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Translation of Biomedical Terms by Inferring Rewriting Rules

Author: Claveau, Vincent
Edition/Format:   Downloadable archival material : English
Publication:Information Retrieval in Biomedicine: Natural Language Processing for Knowledge Integration
Summary:
This chapter presents a simple yet efficient approach to translate automatically unknown biomedical terms from one language into another. This approach relies on a machine learning process able to infer rewriting rules from examples, that is, from a list of paired terms in two studied languages. Any new term is then simply translated by applying the rewriting rules to it. When different translations are produced by  Read more...
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Genre/Form: scientific book chapter
Material Type: Internet resource
Document Type: Internet Resource, Archival Material
All Authors / Contributors: Claveau, Vincent
OCLC Number: 852918463
Language Note: English

Abstract:

This chapter presents a simple yet efficient approach to translate automatically unknown biomedical terms from one language into another. This approach relies on a machine learning process able to infer rewriting rules from examples, that is, from a list of paired terms in two studied languages. Any new term is then simply translated by applying the rewriting rules to it. When different translations are produced by conflicting rewriting rules, we use language modeling to single out the best candidate. The experiments reported here show that this technique yields very good results for different language pairs (including Czech, English, French, Italian, Portuguese, Spanish and even Russian). The author also shows how this translation technique could be used in a cross-language information retrieval task and thus complete the dictionary-based existing approaches.

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