从医学语料库构建克罗地亚医学词典

IF 0.1 0 LANGUAGE & LINGUISTICS
Rasprave Pub Date : 2020-10-30 DOI:10.31724/rihjj.46.2.17
Kristina Kocijan, Silvia Kurolt, Linda Mijic
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引用次数: 4

摘要

该项目的总体目标是根据语料库的类型,在健康领域的词汇和句法层面定义语言模型。在该项目的第一阶段,编制了医学语料库A - MedCorA的文本(克罗地亚现有药物的2,232项药物说明)。对语料库中发现的术语进行分析,定义医学领域内的语义子域(解剖学、病症、微生物、化学等)并将其添加到词典条目中。这些词典资源被用作第二阶段的基础,在第二阶段中,构建NooJ形态学语法,允许在语料库中注释医学术语。所述语法的建立是为了允许识别拉丁字母,以及以克罗地亚大小写结尾的拉丁表达式,而不仅仅是克罗地亚单词。准备好的资源可以通过Sketch Engine提供给更广泛的科学界,用于医学领域的进一步研究,从而能够进一步研究和开发算法,其中包括医疗文件分类、医学文本信息检索或医疗文件的机器翻译,同时考虑到质量和可靠性以及术语的可变性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Building Croatian Medical Dictionary from Medical Corpus
The overall objective of this project is to define linguistic models at the lexical and syntactic levels that appear in the health domain, depending on the type of corpus. In the first phase of the project, the texts forming the medical corpus A – MedCorA (2,232 pharmaceutical instructions for medicaments available in Croatia) were prepared. The terminology found in this corpus was analyzed and the semantic subdomains (anatomy, condition, microorganism, chemistry, etc.) within the medical domain were defined and added to the dictionary entries. These dictionary resources were used as the foundation for the second phase in which NooJ morphological grammars were built allowing annotation of medical terminology in the corpus. Said grammars were built to allow for recognizing Latinisms, as well as Latin expressions written with Croatian case endings, not only Croatian words. Prepared resources are made available to a broader scientific community via Sketch Engine for further research in the field of medicine enabling additional research and development of algorithms for, among others, medical documents classification, medical texts’ information retrieval or machine translation of medical documentation, taking into account quality and reliability as well as terminology variability.
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来源期刊
Rasprave
Rasprave LANGUAGE & LINGUISTICS-
CiteScore
0.70
自引率
50.00%
发文量
29
审稿时长
16 weeks
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