Automatic Population of Italian Medical Thesauri: a Morphosemantic Approach

被引：1

作者：

Amato, Flora ^{[1
]}

Elia, Annibale ^{[2
]}

Maisto, Alessandro ^{[2
]}

Mazzeo, Antonino ^{[1
]}

Pelosi, Serena ^{[2
]}

机构：

[1] Univ Napoli Federico II, Dept Elect Engn & Informat Technol, I-80125 Naples, Italy

[2] Univ Salerno, Dept Polit Social & Commun Sci, I-84084 Fisciano, Italy

来源：

2014 NINTH INTERNATIONAL CONFERENCE ON P2P, PARALLEL, GRID, CLOUD AND INTERNET COMPUTING (3PGCIC) | 2014年

关键词：

FORMS;

D O I：

10.1109/3PGCIC.2014.89

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

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.

引用

页码：432 / 436

页数：5

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