Literature DB >> 10384521

Automatic extraction of linguistic knowledge from an international classification.

R Baud1, C Lovis, A M Rassinoux, P A Michel, J R Scherrer.   

Abstract

Automatic extraction of knowledge from large corpus of texts is an essential step toward linguistic knowledge acquisition in the medical domain. The current situation shows a lack of computer-readable large medical lexicons, with a partial exception for the English language. Moreover, multilingual lexicons with versatility for multiple languages applications are far from reach as long as only manual extraction is considered. Computer-assisted linguistic knowledge acquisition is a must. A multilingual lexicon differs from a monolingual one by the necessity to bridge the words in different languages. A kind of interlingua has to be built under the form of concepts to which the specific entries are attached. In the present approach, the authors have developed an intelligent rule-based tool in order to focus on a multilingual source of medical knowledge, like the International Classification of Disease (ICD) which contains a vocabulary of some 20,000 words, translated in numerous languages.

Entities:  

Mesh:

Year:  1998        PMID: 10384521

Source DB:  PubMed          Journal:  Stud Health Technol Inform        ISSN: 0926-9630


  8 in total

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5.  Evaluating the UMLS as a source of lexical knowledge for medical language processing.

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7.  Heuristic sample selection to minimize reference standard training set for a part-of-speech tagger.

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8.  Creating a medical English-Swedish dictionary using interactive word alignment.

Authors:  Mikael Nyström; Magnus Merkel; Lars Ahrenberg; Pierre Zweigenbaum; Håkan Petersson; Hans Ahlfeldt
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  8 in total

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