Automatic Population of Italian Medical Thesauri: A Morphosemantic Approach

F. Amato, A. Elia, Alessandro Maisto, A. Mazzeo, Serena Pelosi
{"title":"Automatic Population of Italian Medical Thesauri: A Morphosemantic Approach","authors":"F. Amato, A. Elia, Alessandro Maisto, A. Mazzeo, Serena Pelosi","doi":"10.1109/3PGCIC.2014.89","DOIUrl":null,"url":null,"abstract":"In the age of Semantic Web, one of the most valuable challenges is the one connected with the information extraction from raw data. Information must be managed with sophisticated linguistic and computational architectures, which are able to approach the semantic dimension of words and sentences. In this paper we propose a morphosemantic method for the automatic creation and population of medical lexical resources. Our approach is grounded on a list of neoclassical formative elements pertaining to the medical domain an on a large sized corpus of medical diagnoses. The outcomes of this work are automatically built electronic dictionaries and thesauri and an annotated corpus for the NLP in the medical domain.","PeriodicalId":395610,"journal":{"name":"2014 Ninth International Conference on P2P, Parallel, Grid, Cloud and Internet Computing","volume":"150 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 Ninth International Conference on P2P, Parallel, Grid, Cloud and Internet Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/3PGCIC.2014.89","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

Abstract

In the age of Semantic Web, one of the most valuable challenges is the one connected with the information extraction from raw data. Information must be managed with sophisticated linguistic and computational architectures, which are able to approach the semantic dimension of words and sentences. In this paper we propose a morphosemantic method for the automatic creation and population of medical lexical resources. Our approach is grounded on a list of neoclassical formative elements pertaining to the medical domain an on a large sized corpus of medical diagnoses. The outcomes of this work are automatically built electronic dictionaries and thesauri and an annotated corpus for the NLP in the medical domain.
意大利医学辞典的自动人口:一种形态语义学方法
在语义网时代,从原始数据中提取信息是最有价值的挑战之一。信息必须通过复杂的语言和计算架构来管理,这些架构能够接近单词和句子的语义维度。本文提出了一种用于医学词汇资源自动生成和填充的词素语义方法。我们的方法基于与医学领域相关的新古典主义形成要素列表和大型医学诊断语料库。这项工作的结果是自动构建电子词典和词典,并为医学领域的NLP提供一个注释语料库。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信