Natural Language Processing methods and systems for biomedical ontology learning.

Natural Language Processing methods and systems for biomedical ontology learning.
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DOI:
10.1016/j.jbi.2010.07.006
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发表时间:
2011-02
影响因子:
4.5
通讯作者:
Crowley RS
Crowley RS
中科院分区:
医学3区
文献类型:
--
作者:
Liu K;Hogan WR;Crowley RS

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虽然生物医学信息学社区广泛承认领域本体的实用性,但仍然存在许多有效使用的障碍。领域本体的一个重要要求是它们必须实现对领域概念和概念关系的高度覆盖。然而,这些本体的开发通常是一个手动、耗时且经常容易出错的过程。有限的资源会导致概念和关系的缺失,以及随着知识的变化而难以更新本体。在自然语言处理、信息提取、信息检索和机器学习领域中开发的方法提供了用于自动化从自由文本文档中丰富本体的技术。在这篇文章中,我们回顾了现有的方法和开发的系统,并讨论了现有的方法如何有利于生物医学本体的发展。
While the biomedical informatics community widely acknowledges the utility of domain ontologies, there remain many barriers to their effective use. One important requirement of domain ontologies is that they must achieve a high degree of coverage of the domain concepts and concept relationships. However, the development of these ontologies is typically a manual, time-consuming, and often error-prone process. Limited resources result in missing concepts and relationships as well as difficulty in updating the ontology as knowledge changes. Methodologies developed in the fields of natural language processing, information extraction, information retrieval and machine learning provide techniques for automating the enrichment of an ontology from free-text documents. In this article, we review existing methodologies and developed systems, and discuss how existing methods can benefit the development of biomedical ontologies.
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