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Morphosemantic strategies for the automatic enrichment of Italian lexical databases in the medical domain

机译:在医学领域自动丰富意大利词汇数据库的形态学策略

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Because of the importance of the information conveyed by the clinical documents and owing to the large quantity of raw texts produced in the healthcare system, it became a determinant challenge, in the NLP research field, to arrange the extraction and the management of meaningful data, starting from real text occurrences. In this paper we approach a corpus of 5000 medical diagnoses with sophisticated linguistic and computational devices, which are able to access the semantic dimension of words and sentences contained in it. Our morphosemantic method is grounded on a list of neoclassical formative elements pertaining to the medical domain which has been used for the automatic creation and population of medical lexical resources. The outcomes of this work are automatically built electronic dictionaries and thesauri and an annotated corpus for the NLP in the medical domain.
机译:由于临床文件所传达信息的重要性,并且由于医疗保健系统中产生了大量原始文本,因此在NLP研究领域,安排有意义的数据的提取和管理已成为决定性的挑战,从真实的文字出现开始。在本文中,我们使用复杂的语言和计算设备处理了5000个医学诊断的语料库,这些设备能够访问其中包含的单词和句子的语义范围。我们的形态语义学方法基于一系列与医学领域有关的新古典形成要素,这些要素已用于自动创建和填充医学词汇资源。这项工作的结果是自动建立电子词典和叙词表,并为NLP在医学领域提供注释的语料库。

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